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https://renderman.pixar.com/stories/the-world-of-coco

Key Notes:
- Disney's Renderman was not optimized by the world of the movie thus the time it took to render a frame was 1000 hours since the scene contained 8 million lights which is an overwhelming amount for Disney's rendering software.
- The team managed to reduce the render time from 1000 hours to 50 hours a frame by developing a new system that would essentially render the closest lights to their full quality and give a bare minimum render to lights that are far away from the scene.

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Written by Mike Seymour

Challenges and Ambitions in Lighting

RenderMan tackled some of the most complex rendering scenes yet attempted by Pixar, in the Oscar winning Coco. The 2017 film is based on an original idea by Lee Unkrich and is directed by Unkrich and co-directed by Adrian Molina. It tells the story of a 12-year-old boy, Miguel Rivera, who is accidentally transported to the land of the dead, where he seeks the help of his deceased musician great-great-grandfather to return him to his family and the living. The concept of the film is based on the Mexican holiday of[el] Día de los Muertos orthe Day of the Dead. In the 'afterlife' environment the team at Pixar needed to produce a layered and complex environment with an incredible array of lights.

The main afterlife city of the Land of the Dead in Coco is based on the real world city Guanajuato in Mexico that the team visited during pre-production. Director Unkrich conducted an early research trip to Mexico with Pixar head of story Jason Katz, production designer Harley Jessup and Pixar producer Darla K. Anderson, visiting Mexico City, Morelia, Oaxaca and Guanajuato. Guanajuato's brightly terraced architecture on steep hillsides became the dominant reference, both for its colourful houses and the view at night when the hillside lit up.

The Pixar city extrapolated the hillside idea, with The City of the Dead's layout being very much a vertical city, which contrasted with the film's depiction of Miguel's very flat hometown.

Interestingly, Pixar's team came up with a set of rules for the design of the city. In addition to being vast in scope, it was built for the dead, so there are no handrails or safety barriers, as the inhabitants are already dead. The city is a mix of styles and periods representing its citizens and their timelines.

One the most complex aspects of the film was the scope and use of lights. 29,000 lights were used in the train station scene. The cemetery had 18,000 lights and the City of the Dead used 2,000 practical lights in RenderMan. The studio team used the RenderMan API to create 700 special point cloud lights, which, when expanded, is equivalent to 8.2 million lights.

Lightspeed Team

At Pixar there is a special 'Lightspeed team' for each film. These teams sit between the tools team and the production, and they focus on solving project specific problems. For Coco the lead was Renee Tam. Her team was responsible for anything that might go wrong or slow down the film's production. Her team was also responsible for any project based R&D. At Pixar, if something is found to have an unacceptable long render time then the Lightspeed is given the task of solving the problem. Render time issues can involve aspects in RenderMan or how the production is working with RenderMan.

"We were like 'Holly cow, this is something we have never done before"

-Renee Tam, LightSpeed Lead on Coco

"Our department is responsible for research and development work to bring down the render time, or write new tools in the production pipeline to streamline whatever is needed", explained Tam. In addition to the core Lightspeed team, the RenderMan team normally assigns a couple of their own team's engineers to help with the enormous complexity of any Pixar film, This also allows the team to take lessons learnt from real world production back into the general implementation of RenderMan.

For example, when Coco first started the team looked at concept images from the art department, and the vast amount of lights in the concept art. "We were like 'Holly cow, this is something we have never done before" recalls Tam, "And so at that very moment, we started working with the RenderMan team, and they were awesome". The team outlined the seemingly impossible problem of rendering shots with so many lights. "At the very beginning we told them that Coco would need "a lot of lights", but I never told them what that actually meant," Tam laughingly recalls. The problem was not just the number but also the complexity as the production team wanted to maintain control over the vast array of lights, including the ability to have gels, gobos and blockers (barn doors), in fact anything that generic lights could have in RenderMan normally. In the old PRMan the vast lighting plans in the Coco storyboards and concept art, would have been impossible to implement.

The Lightspeed team did a test with the old PRMan and it was beyond unworkable for what the production needed, in fact, the tests could never successfully complete a render. "So the RenderMan team went back and thought about the problem and came back with a proposal for a new lighting schema that would lower the render time substantially." However the team hadn't actually seen any concept art themselves. "Anyway they came back after a little time and we tried the new schema, and we told them great - it does now render but it takes 1000 hours a frame to get anything that looks like something we might want, and it was still really noisy." she explains. "When we showed the RenderMan team they were confused, - why would it take so long they asked? And then they looked at our setup and said 'wait a second - how many lights do you call 'a lot of lights' and I answered; at last count we had instanced our lights out to about 8 million lights. At that point we all went into a second round of R&D!"

The team did solve the problem, together they worked out a new point cloud lighting system. The new approach dispensed with some filtering, it also ignored lights that, due to position, could not contribute, and it reduced complexity on distant point cloud lights. The giant point light set system takes advantage of an Octree system that sampled the lights more efficiently. It then integrated with a new lighting picking system which focuses on the closer lights to have more articulated controls. After 6 months the Lightspeed and RenderMan team had a system that gives the effect of millions of lights and took the notional render time on the complex shots down from 1000 hours to 450 hours. The team continued and reduced this further to 125 hours and finally 75 hours a frame. With some additional work on the way the production team worked with the lighting in shots, the final per frame time at the end of production was just 50 hours per frame.

The Lightspeed team did other innovative lighting developments. Tam explained at Siggraph Asia last year how her team also took advantage of the Firefly special tool, that they had developed on The Good Dinosaur, that could bind sets of different lights to the same object. This was then improved for use in Coco: City of the Dead scenes, and it proved very effective. Other improvements from the Lightspeed team went into Presto and other areas, not render related.

RenderMan

RenderMan's current version is 21.7. The RIS technology in the current RenderMan is a highly-optimized framework for rendering heavy geometry, hair, volumes, and irradiance with incredible efficiency in a single pass.

RenderMan has established itself as one of the most flexible, powerful, and reliable tools for rendering cinematic imagery. RenderMan's RIS framework was designed from the outset to trace rays as fast as possible. With a new framework consisting of integrators, BRDF's (written in C++), and intelligent light services. RIS is allowing RenderMan to set new standards for both speed and memory efficiency when rendering complex production scenes such as the ones In Coco. RenderMan v22 is expected to be released and shown at SIggraph 2018 later this year. RenderMan's next film from Pixar is the Incredibles 2, to be released in June.

The film Coco has received praise for its animation, vocal performances, musical score, songs, emotional story and respect to Mexican culture. It earned numerous accolades, including winning Best Animated Feature (and Best Song) at this year's 90th Academy Awards. The film has also won the 2018 BAFTA for best animated film.

Escrito por Mike Seymour y traducido por Leif Pedersen.

retos y Ambiciones de iluminacion

RenderMan abordó algunas de las escenas de renderizado más complejas que ha intentado Pixar en la pelicula Coco, la cual ha sido galardonada con el Oscar. La pelicula está basada en una idea original de Lee Unkrich y está dirigida por Unkrich y co-dirigida por Adrian Molina. Coco cuenta la historia de un niño de 12 años, Miguel Rivera, que accidentalmente es transportado a la Tierra de los Muertos, donde busca la ayuda de su fallecido músico tatararbuelo para devolverlo a su familia y los vivos. El concepto de la película se basa en la fiesta mexicana del Día de los Muertos. En el mundo de los muertos, el equipo de Pixar necesitaba producir un entorno complejo y con una increíble variedad de luces.

La principal ciudad de la Tierra de los Muertos en Coco se basa en la ciudad real de Guanajuato en México, la cual visitó el equipo creativo durante la preproducción. El Director Unkrich realizó un temprano viaje de investigación a México con el jefe de historia de Pixar, Jason Katz, la diseñadora de producción Harley Jessup y la productora de Pixar, Darla K. Anderson, los cuales visitaron la Ciudad de México, Morelia, Oaxaca y Guanajuato. La arquitectura de las amplias terrazas de Guanajuato en sus empinadas laderas se convirtió en la referencia principal, tanto por sus coloridas casas como por las increibles laderas iluminadas de noche.

La ciudad de Pixar extrapoló la idea de la ladera, trazando La Tierra de los Muertos como una ciudad vertical, que contrastaba con la ciudad natal de Miguel, la cual era mucho mas plana.

Curiosamente, el equipo de Pixar ideó un conjunto de reglas para el diseño de la ciudad. Además de ser enorme, fue construida para los muertos, por lo que no hay barandillas o barreras de seguridad, ya que los habitantes ya están muertos. La ciudad es una mezcla de estilos y períodos que representan a sus ciudadanos y sus líneas de tiempo.

Uno de los aspectos más complejos de la película fue el inmenso uso de luces. 29,000 luces se usaron en la escena de la estación de tren. El cementerio tenía 18,000 luces y la Ciudad de los Muertos usó 2,000 luces prácticas en RenderMan. El equipo del estudio utilizó la API de RenderMan para crear 700 luces especiales de nubes de puntos (point cloud), que, cuando se expanden, equivalen a 8,2 millones de luces.

Equipo Lightspeed (velocidad de la luz)

En Pixar hay un "equipo Lightspeed" especial para cada película. Estos equipos existen entre el equipo técnico y la producción, y se enfocan en resolver problemas específicos del proyecto. Para Coco, el equipo fue liderado por Renee Tam. Su equipo era responsable de cualquier cosa que pudiera salir mal o afectar las metas de la producción de la pelicula. Su equipo también fue responsable de cualquier proyecto de investigacion y desarrollo technologico (R&D). En Pixar, si se descubre que algo tiene un tiempo de renderización inaceptable, se le da a Lightspeed la tarea de resolver el problema. Los problemas de tiempo de renderizado pueden involucrar aspectos en RenderMan o el uso que le dan los artistas.

"Estabamos muy sorprendidos, nos hizo enfrentar retos que nunca antes habiamos abordado"

-Renee Tam, Lider de LightSpeed en Coco

"Nuestro departamento es responsable del trabajo de investigación y desarrollo para reducir el tiempo de renderizado, o crear nuevas herramientas en la línea de producción para agilizar lo que sea necesario", explicó Tam. Además del equipo principal de Lightspeed, el equipo de RenderMan normalmente asigna a varios ingenieros de su propio equipo para ayudar con la enorme complejidad en cada película de Pixar. Esto le permite al equipo de RenderMan implementar las lecciones aprendidas en la version general de RenderMan.

Por ejemplo, cuando Coco comenzó, el equipo analizó las imágenes conceptuales del departamento de arte y la gran cantidad de luces en el arte conceptual. "Estabamos muy sorprendidos, nos hizo enfrentar retos que nunca antes habiamos abordado", recuerda Tam, "Y en ese mismo momento, comenzamos a trabajar con el equipo de RenderMan, y la colaboracion fue increíble". El equipo delineó el problema aparentemente imposible de hacer tomas con tantas luces. "Al principio les dijimos que Coco necesitaría "muchas luces", pero nunca les dije lo que realmente significaba", recuerda Tam riendo. El problema no era solo el número de luces, sino también la complejidad, ya que el equipo de producción quería mantener el control sobre la amplia gama de luces, incluyendo la capacidad de tener geles, gobos y bloqueadores (formas de colorear y manipular luces), sin comprometer las herramientas usadas normalmente por los artistas en RenderMan.

En antiguas versiones de RenderMan, las grandes ambiciones gráficas y el arte conceptual de Coco hubieran sido imposibles de implementar. El equipo de Lightspeed hizo una prueba con una version de RenderMan anterior y no era factible para lo que la producción necesitaba, de hecho, las pruebas nunca pudieron completar un render. "Así que el equipo de RenderMan volvió y pensó sobre el problema y regresó con una propuesta para un nuevo esquema de iluminación que reduciría sustancialmente el tiempo de renderización". Sin embargo, el equipo technico no había visto ningún concepto de arte. "Después de un tiempo volvieron con una solucion, y ​​les dijimos que funcionaba bien, pero se necesitaban 1000 horas por cada cuadro, y tenia mucho ruido" ella explica. "Cuando le mostramos los resultados al equipo de RenderMan estaban confundidos, no se entendian por que tardaba tanto...y luego de mirar nuestra configuración dijeron...espera un segundo, cuántas luces llamas 'muchas luces' y yo respondí; en el último recuento teniamos alrededor de 8 millones de luces. ¡En ese momento todos entramos en una segunda ronda de investigacion y desarrollo!"

Despues de mucha colaboración, el equipo resolvió el problema y elaboraron un nuevo sistema de iluminación de nube de puntos. Este nuevo sistema prescindió de algunos filtros, también ignoró las luces que no contribuian a la toma debido a su posicion, y redujo la complejidad de las luces distantes. El sistema de luz de puntos aprovecha un sistema Octree, el cual evalua las luces de manera más eficiente. Luego se integró con un nuevo sistema de selección de iluminación, el cual le entregaba un mayor enfoque y herramientas de articulacion a las luces más cercanas. Después de 6 meses, el equipo Lightspeed y RenderMan tenía un sistema que proporcionaba el efecto de millones de luces y reducia el tiempo de renderización en las tomas mas coplejas de 1000 horas a 450 horas. El equipo continuó sus investigaciones y logro reducir los tiempos aun mas, de 125 horas a finalmente 75 horas por cuadro. Con un poco de trabajo adicional en la forma en que el equipo de producción trabajó con la iluminación en las tomas, el tiempo final por cuadro fue de solo 50 horas en las tomas mas complejas.

El equipo de Lightspeed hizo otros desarrollos de iluminación innovadores. Tam explicó el año pasado en Siggraph Asia cómo su equipo también aprovechó la herramienta especial Firefly, que habían desarrollado en The Good Dinosaur, que podía unir conjuntos de diferentes luces al mismo objeto. Esto fue mejorado para su uso en Coco: especialmente en las escenas de la Ciudad de los Muertos, y resultó ser muy efectivo. Otras mejoras del equipo Lightspeed entraron en Presto (programa de animacion en Pixar) y otras áreas no relacionadas con renderización.

RenderMan

La tecnología RIS en la version actual de RenderMan (21.7) es un marco altamente optimizado para renderizar geometría compleja, cabello, volúmenes e irradiancia en una sola pasada ​​con una eficiencia increíble.

RenderMan se ha establecido como una de las herramientas más flexibles, potentes y confiables para renderizar imágenes cinematograficas. El marco de RIS de RenderMan se diseñó desde el principio para rastrear rayos lo más rápido posible. Con un nuevo marco que consiste en integradores, BRDF (escrito en C ++) y servicios inteligentes de luz. RIS le permite a RenderMan establecer nuevos estándares para la velocidad y la eficiencia de la memoria al renderizar escenas de producción complejas como las de Coco. Se espera que la version 22 de RenderMan se publique y se muestre en unos meses mas durante Siggraph 2018. La proxima pelicula de Pixar es The Incredibles 2, que se lanzará en junio del 2018, y es el proximo reto de RenderMan.

La película Coco ha recibido elogios por su animación, historia emocional, actuaciones vocales, musica y su respeto a la cultura mexicana. Obtuvo numerosos elogios, incluidos el premio a la Mejor Película de Animación y Mejor Canción en los Premios Oscar y el premio BAFTA 2018 a la mejor película animada.

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Written by Mike Seymour Challenges and Ambitions in Lighting RenderMan tackled some of the most complex rendering scenes yet attempted by Pixar, in the Oscar winning Coco. The 2017 film is based on an original idea by Lee Unkrich and is directed by Unkrich and co-directed by Adrian Molina.

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https://developer.nvidia.com/nvidia-rt-denoiser

Key Notes:
-ReBLUR - Provides more realistic lighting with better temporal stability (Anti-aliasing) and is 50% faster

-SIGMA - A fast shadow denoiser. this can denoise shadows from any type of light sources such as sunlight or local lights

-ReLAX - Denoises raytraced signals in the scene which yields better anti-aliasing and is very responsive to changing light conditions. ReLAX offers substantial improvements to image quality and performance

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NVIDIA GTC 2021 (Nov 8-11). Attend technical training and sessions for game developers. REGISTER FOR FREE NVIDIA Real-Time Denoisers The NVIDIA Real-Time Denoisers (NRD) are a spatio-temporal API agnostic denoising library that’s designed to work with low ray per pixel signals. It uses input signals…

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https://docs.blender.org/manual/en/latest/render/layers/denoising.html#:~:text=Denoising%20filters%20the%20resulting%20image,detail%20as%20well%20as%20possible.

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Denoising filters the resulting image using information (known as feature passes)
gathered during rendering to get rid of noise, while preserving visual detail as well as possible.

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Maya vs Blender - 8 Amazing Differences You Should Know

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In this article Maya vs Blender , we will look at their Meaning, Head to Head Comparisons, Key differences in detail to understand easily.

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Example of render time using Arnold in Maya 

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Example of render time using Arnold in Maya 

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https://www.youtube.com/watch?v=n87U29SOapQ&t=3s

Key Notes:
-16 seconds but quality is bad
-3:45 min for better quality

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How to reduce your Arnold render time in Maya up to 50%

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https://docs.arnoldrenderer.com/display/A5AFMUG/Arnold+Denoiser

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Arnold Denoiser - Arnold for Maya User Guide - Arnold Renderer

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https://docs.chaos.com/display/VMAYA/Denoiser#expand-UIPathDisplayRenderSettingsbuttonRenderElementstabDenoiser

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The V-Ray Denoiser Render Element removes noise from other render elements and saves its results in a few different ways.

Overview

The V-Ray Denoiser takes an existing render and applies a denoising operation to it after the image is completely rendered out via normal means. The denoising operation detects areas where noise is present and smooths them out. Images can also be denoised using the Standalone Denoise Tool included with the installation of V-Ray for Maya.

Because the V-Ray Denoiser operates on other render elements (like RGB_Color ) rather than being part of the rendering process itself, the denoising operation does not require re-rendering of the scene.

There are three denoising engines to choose from - the Default V-Ray denoiser, the NVIDIA AI denoiser (V-Ray's implementation of NVIDIA's AI-based denoising algorithm) and the Intel Open Image denoiser (V-Ray's implementation of the Intel® Open Image Denoise). See the Denoising Engines section for more information.

The V-Ray Denoiser has three preset options for its settings: Default, Mild, and Strong. Parameters can also be adjusted directly by using the Custom preset.

UI Path: ||Display Render Settings button|| > Render Elements tab > Denoiser

To use render elements, select from the Available render elements column and click the Add button to add the passes you wish to generate at render time. When you render the scene, the added render elements listed in the column on the right, will also render, which can be viewed from the VFB window's channel drop-down menu.

For more information on the parameters on this dialog, see the Render Elements tab page.

Using the Denoiser

When rendering, the V-Ray Denoiser automatically adds a few render elements in the V-Ray frame buffer which are required by the denoising algorithm. Some of them are standard render elements like Diffuse and Reflection Filter. A few special render elements are also generated:

The noiseLevel render element is the amount of noise for each pixel in greyscale values, as estimated by the V-Ray image sampler.

The defocusAmount render element is non-black only when depth of field and motion blur are enabled, and contains the estimated pixel blurring in screen space.

The VRayDenoiser render element, when generated, contains the final image that results from noise removal. Whether this render element is generated depends on the Mode selection.

Denoising Engines

VRayDenoiser offers a choice between the Default V-Ray denoiser, the NVIDIA AI denoiser and the Intel Open Image denoiser. Each offers a different denoising algorithm that comes with different benefits.

Default V-Ray denoiser - V-Ray's denoising algorithm. It can utilize the CPU or the GPU (AMD or NVIDIA GPUs) to perform the denoising. It is consistent when denoising render elements, as it applies the same denoising operator to all render channels. This means that it is recommended for denoising the render elements to be used for compositing back the beauty image. In addition, it comes with a Denoiser Tool, which is recommended for denoising animation by using frame blending.

AI-based denoising algorithm. The NVIDIA AI denoiser NVIDIA AI denoiser - V-Ray's integration of NVIDIA's an NVIDIA GPU to work, regardless of whether the actual rendering was performed on the CPU or GPU. This means that rendering on the CPU will still require an NVIDIA GPU for denoising with the NVIDIA AI denoiser and has some advantages and drawbacks compared to the Default V-Ray Denoiser. For example, the NVIDIA AI denoiser performs the denoising faster, but is not consistent when denoising render elements. This means that there will be differences between the original RGB image and the one reconstructed from render elements that are denoised with the NVIDIA AI denoiser. It also doesn't support cross-frame denoising and will likely produce flickering when used in animation.

The NVidia AI denoiser only works on Nvidia Maxwell and newer GPU architectures. If no proper devices are found, V-Ray will silently fall back to the Default V-Ray denoiser.

You can select which GPU device(s) to be used by the NVIDIA AI denoiser with the following environment variable - VRAY_OPTIX_DENOISER_PLATFORMS. For more information, see the Environment Variables page.

Intel Open Image denoiser - V-Ray's integration of Intel Open Image Denoise. The Intel Open Image denoiser works with your CPU device and does not use hardware acceleration.

Attributes

The parameters for this render element appear in the Attribute Editor under Extra V-Ray Attributes.

Enabled - Enables the render elements to appear in the V-Ray Virtual Frame Buffer.

Deep output - Specifies whether to include this render element in deep images.

Filename suffix - The text added to the end of the rendered file, when saved as a separate file (e.g. myrender.denoiser.vrimg).

Mode - Specifies how the results of VRayDenoiser will be saved.

Only generate render elements - All render elements required for denoising are generated so that denoising can be done with the Standalone Denoise Tool or the V-Ray Denoiser plugin for Nuke. The information calculated within them is not applied to other render elements, and no VRayDenoiser Render Element is generated.
Hide denoiser element - The VRayDenoiser channel is not present separately in the VFB. The effectsResult channel is generated with the denoised image.
Show denoiser element - The VRayDenoiser Render Element is generated to contain a denoised version of the RGB Color Render Element using the specified settings. The original render elements, including the RGB Color Render Element, are not changed.

Engine - Allows choosing the production denoise engine. Available options are:

Default V-Ray denoiser;
NVIDIA AI denoiser; Note that, the NVIDIA AI denoiser requires an NVIDIA GPU.
Intel Open Image denoiser.

IPR Engine - Allows choosing the denoise engine during IPR. Available options:

NVIDIA AI denoiser; Note that, the NVIDIA AI denoiser requires an NVIDIA GPU.
Intel Open Image denoiser.

Preset - Offers to automatically set Strength and Radius values. Available only for the Default V-Ray Denoiser.

Default - Applies mid-level denoising.
Mild - Applies a more subtle level of denoising than the Default preset.
Strong - Applies a stronger level of denoising than the Default preset.
Custom - Allows the Strength and Radius parameters to be set to custom values.

Strength - Determines the strength of the denoising operation. This value is automatically set by preset selection, but can be changed when Preset is set to Custom.

Radius - Specifies the area around each pixel to be denoised. A smaller radius affects a smaller range of pixels, while a larger radius affects a larger range, which increases the noise removal. This value is automatically set by preset selection, but can be changed when Preset is set to Custom.

Hardware acceleration - Uses the GPU device(s) to accelerate the denoising calculations. In case there is no compatible GPU device, denoising will automatically fall back to use the CPU, even if the option is enabled. This option is only available for the Default V-Ray Denoiser.

Update - Re-apply the denoising operation when the required render elements are already present in the V-Ray frame buffer. The elements can be either generated from a render in Maya, or by loading a multi-channel . vrimg or OpenEXR into the V-Ray Frame Buffer. Use this button to apply denoising again after settings on this rollout have been changed.

Suggested Render Settings

While the denoiser can be quite effective at removing noise, it is not perfect. Very noisy images can lead to artifacts and loss of image detail. For most scenes, use the Progressive image sampler with the Noise threshold parameter set to 0.05 or lower. Additionally, the denoiser works best when the noise levels across the image are similar (when the noiseLevel channel is as close to uniform gray as possible), so using very low sampling is not recommended.

When rendering animations, disabling the Animated noise pattern option in the DMC sampler rollout generally improves the results.

Using the Standalone Denoise Tool on the rendered frames can additionally improve the quality of the animation.

You can modify the frequency at which the denoiser is updated during progressive rendering via the Post effect rate parameter located in V-Ray's Settings > System > Post effects rollout.

During IPR, the Post effect rate is set to 100 by default.

Example: Default V-Ray denoiser

The example below illustrates how the Default V-Ray denoiser works after more samples are made with the Progressive image sampler. When the samples are too few, there's not enough information for the denoising to produce a smooth result.

The original vs. the denoised image after 64 passes.

Example: NVIDIA AI denoiser

The example below illustrates how the NVIDIA AI denoiser works after more samples are made with the Progressive image sampler. When the samples are too few, there's not enough information for the denoising to produce a smooth result.

The original vs. the denoised image after 64 passes.

Example: Intel Open Image Denoiser

The example below illustrates how the Intel Open Image denoiser works after more samples are made with the Progressive image sampler. When the samples are too few, there's not enough information for the denoising to produce a smooth result.

The original vs. the denoised image after 64 passes.

Denoising Separate Render Elements

To denoise a separate Render Element, select it from Render Settings > Render Elements > Added Render Elements.

In the Attribute Editor, go to Extra Vray Attributes and enable the Denoise option.

Some render elements don't have a Denoise option, as they don't produce color information. For this reason, it makes no sense to denoise them, as this would distort the data. For example, ZDepth and Velocity data doesn't need denoising, just like masks like the Cryptomatte or the MultiMatte don't either. For more information, please see the respective render element page.

Denoising Animations

When denoising animations, it is recommended to use the Standalone Denoiser Tool. Unlike the denoiser integrated in the UI, the standalone tool can do frame blending for animations, which reduces flickering. The integrated denoiser only works on the rendered frame and does not take the next and previous frame(s) into account, like the standalone tool does.

To denoise an image sequence with vdenoise run the following command:

vdenoise -inputFile="path\to\sequence_????.ext

where the question mark (?) replaces the digits in the sequence's file names.

For example, if the images in the sequence are named anim_0001.exr, anim_0002.exr, etc. and are located in the folder c:\renderoutput, the full command will be:

vdenoise -inputFile="c:\renderoutput\anim_????.exr

When that command is run, the sequence is read and for each frame, the specified number of adjacent frames are also considered. A new output image is then written for each frame.

Recommended settings:

Мode set to only generate render elements.

denoising engine set to Default V-Ray denoiser.

Render output set to vrimg or multichannel exr.

The NVIDIA AI denoiser does not perform frame blending and will likely produce flickering when denoising animations.

Denoising in IPR

When denoising IPR renders, it is recommended to use the NVIDIA AI or the Intel Open Image denoiser. Both of the engines ensure fast denoised results.

To use the denoiser in IPR with the VFB, add a Denoiser render element and select an IPR Engine.

To use the denoiser with Viewport IPR:

1. Add a Denoiser render element and choose an IPR Engine.

2. Start V-Ray IPR in the Maya viewport using the V-Ray logo icon in the viewport:

3. Enable the viewport denoiser by clicking the Denoiser icon ( ) next to the V-Ray logo.

Notes

Image denoising takes place after the frame has been rendered, so the results of denoising will not show up until all rendering has finished.

Textures or materials such as VRayStochasticFlakesMtl that could be considered to have a purposely noisy look are not considered "noisy" by vrayRE_Denoiser, and are not affected by the noise removal process.

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The V-Ray Denoiser Render Element removes noise from other render elements and saves its results in a few different ways. The V-Ray Denoiser takes an existing render and applies a denoising operation to it after the image is completely rendered out via normal means.

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How long does it take to render in Blender

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How long does it take to render in Blender

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https://docs.blender.org/manual/en/2.79/render/workflows/animations.html#:~:text=If%20each%20frame%20takes%2030,12%20hours)%20of%20render%20time.

Key Notes:
-If the total render time is an hour or more, you want to use the “Frame Sequence” approach. For example, if you are rendering a one-minute video clip for the film, there will be (60 seconds per minute) X (24 frames per second) or 1440 frames per minute. If each frame takes 30 seconds to render, then you will be able to render two frames per minute, or need 720 minutes (12 hours) of render time.

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While rendering stills will allow you to view and save the image from the render buffer when
it is complete, animations are a series of images, or frames,
and are automatically saved directly out to a drive after being rendered.

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Real-Time Ray Tracing Using Nvidia OptiX

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Real-Time Ray Tracing Using Nvidia OptiX

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https://diglib.eg.org/bitstream/handle/10.2312/egsh.20101049.065-068/065-068.pdf?sequence=1&isAllowed=y

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https://docs.arnoldrenderer.com/display/A5AFMUG/Introduction+to+Arnold+for+Maya

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Arnold is an advanced Monte Carlo ray tracing renderer built for the demands of feature-length animation and visual effects movies. This is a beginner's tutorial that introduces MtoA, a plug-in that allows you to use the Arnold renderer directly in Autodesk Maya. In this tutorial, w e will cover how to build a simple photographic lighting studio setup that can be used to light and render all manner of objects. We will go through the steps to light, shade and render a toy robot model using the Arnold renderer. We will use Arnold's proprietary lights to achieve a physically accurate, photo-realistic lighting setup. As well as using Arnold's lights, you can also use standard Maya lights when rendering with Arnold. If you select a light and then inspect the Maya attribute editor, as well as the regular light attributes, you will also see a new group of Arnold attributes for the light, which is where any additional settings used by Arnold can be accessed.

We will use the The The Due to a large number of controls, the standard_surface shader to shade the robot and give it a metallic finish. standard_surface shader is a multi-purpose shader capable of producing all types of materials, from simple plastic to car paint or skin. standard_surface shader is split up into several groups such as diffuse, specular, sub-surface scattering, etc. We will need to adjust the diffuse and specular attributes to get a believable brushed metal effect. standard_surface shader is very powerful, and allows a large number of different sorts of materials to be created, but can be somewhat daunting at first.

We will also look at some of Arnold's camera lens options to produce a realistic, physically accurate depth of field. Lastly, we will look at how to optimize render settings and eliminate any noise that may appear in the render. Note that, although Maya and MtoA have been used in this tutorial, much of the material is really about Arnold in general and so is also relevant to users of other Arnold implementations such as 3ds Max to Arnold (MAXtoA) and Houdini to Arnold (HtoA).

The estimated time it will take to complete this tutorial should be no more than 30 minutes.

Start off by opening the Arnold-robot.ma scene. In the scene, you should see the robot model (positioned at 0,0,0 on the Maya grid) and a simple studio backdrop model.

Now we want to light our studio scene. Start off by creating three Ai Area lights. This can be done by clicking on the light icon on the Arnold shelf or by selecting it via the Arnold menu: Arnold-> Lights-> Area Light.

Position one light on either side and another in the center, above the robot. Rotate them so that they are pointing inwards towards the robot as indicated in the screengrab below.

The scene may appear dark when it is rendered. We, therefore, need to increase the exposure of the lights. Under the Arnold attributes, increase the exposure to around 8 for each light.

We can change the color of the lights by enabling Color Temperature. Select the right light and enable the Color Temperature within its Arnold attributes. Leave it at its default temperature value of 6500. This will give a cool blue feel to the light. Select the light on the left and do the same, except change the Color Temperature to a warmer color, something like 4000.

You may notice some noise in the shadows from the Ai Area lights. This is because the light samples are set to 1 by default. To reduce the noise, try increasing the light samples to 3. This setting can be found in the Arnold attributes within each light. Light samples control the quality of the noise in the soft shadows and direct specular highlight. The higher the number of samples, the lower the noise, and the longer it takes to render.

Assign a standard_surface shader to the robot. To turn it into a brushed metal material we will change the following settings. Increase the metalness to around 1 and change the base_color to a mid-grey color and reduce the specular_weight to 0. The specular_roughnesscontrols the glossiness of the specular reflections. The lower the value, the sharper the reflection. Increase it to around 0.5.

We can use Maya's native camera to render the scene using depth of field. Select the render camera and open its Arnold attributes in the attribute editor. Click on 'Enable DOF'. You won't notice any difference in the render unless you increase the 'Aperture Size'. However, you will need to focus the camera on something first. Select the robot's head and go to Display>Heads up display>Object Details. This will show you the distance from the camera that the head model is. Type this value into the 'Focus Distance' attribute. Now when you increase the 'Aperture Size' you should see that the robot's head is in the camera focus. Try a low value, such as 0.05 (this value is scene scale-dependent).

Rendering the scene using the default Camera (AA) setting of 3 is good enough for test renderings. However, for a final render, you will need to increase this to at least 5 or more depending on the amount of depth of field you have set in the scene.

There may be some noticeable specular noise on the surface of the robot due to poor sampling of the indirect specular component of the robot's shader. Increasing the specularsamples to 2 or 3 helps resolve this noise and to create a cleaner looking render.

# data[].attributes.attachment_link.description
Arnold is an advanced Monte Carlo ray tracing renderer built for the demands of feature-length animation and visual effects movies. This is a beginner's tutorial that introduces MtoA, a plug-in that allows you to use the Arnold renderer directly in Autodesk Maya.

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Detailed Workflow Helped Mix Animation, Live Action

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Detailed Workflow Helped Mix Animation, Live Action

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https://www.proquest.com/docview/2436897733/fulltext/90BC1DD4BDF54160PQ/1?accountid=26453

Key Notes:
- The last process where the production simulated hair, fur, feathers, etc. for the animals and had to make sure that the light bounced off realisitcally on the surface of these CG characters could benefit from OptiX as the creative team behind this part of the job would be able to produce multiple samples and experiments to get the best result for the final film.

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Detailed Workflow Helped Mix Animation, Live - ProQuest

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Explore millions of resources from scholarly journals, books, newspapers, videos and more, on the ProQuest Platform.

# data[].attributes.body
https://www.proquest.com/docview/1777473764/fulltext/A28DB71C1E884FF3PQ/1?accountid=26453

Key Notes:
-Aron works with simulated VistaVision optics - the default in Autodesk's Maya, which is used for the majority of the workflow, including model construction and lighting. "We render with [Maya plug-in] Mental Ray," he adds, "and we use [The Foundry's] Nuke for compositing. We try to keep the software list low, because it allows us to be agile."

-Something Kilian and I gravitated toward was Ralph's line work - he did a lot of pencil lines on his paintings. So instead of a lot of geometry in our CG models, we incorporate a lot of surface-drawn lines, which give a nice hand-rendered feel and the [illusion] of detail, which works well for our pipeline and rendering ability."

-Could these renders in the show be improved if the art team were able to make more experiment samples during the pre-production with OptiX which would benefit the show's visuals or reduce timetables as they are able to get results faster.

# data[].attributes.attachment_link.description
Explore millions of resources from scholarly journals, books, newspapers, videos and more, on the ProQuest Platform.

# data[].attributes.body
https://docs.arnoldrenderer.com/pages/viewpage.action?pageId=40111301

Sampling is the process where the software collects information from the scene. This is done by sending out rays from the camera until the ray hits an object in the scene. When that ray hits something it performs some calculations that will eventually return a piece of information about that object such as the colour.

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When working with a renderer like Arnold, it is useful to have a basic understanding of the core principles behind ray-trace rendering. Producing a realistic-looking image of a virtual scene requires simulating the propagation of light in the scene all the way from the light sources to the camera. To determine the color of each image pixel, Arnold collects information from the scene geometry, shaders, lights, etc., and traces a number of random light transport paths that connect the objects seen through the pixel to the light sources - a process called 'sampling'. The quality of the resulting image largely depends on the number of paths, or samples, generated for each pixel.

When rendering an image, Arnold must determine a color value for each pixel by examining the scene. Arnold achieves this by sending out a number of rays from the camera's position until they hit an object in the scene. Every time a ray hits an object, it will perform some calculations that will eventually return a piece of information about the object (its color, for instance). This process can basically be described as 'sampling' the pixels in the virtual camera's image plane.

Renders computed with too few samples in each pixel can be noisy. Increasing the number of samples per pixel gives a less noisy image which better represents the actual scene. The images below show a comparison when increasing the number of Camera (AA) samples in a scene. Not only does increasing Camera (AA) samples reduce aliasing noise, but it also adds more secondary ray samples which also reduces noise in the lighting.

Camera (AA) Sampling

So, what is camera sampling? Basically, a number of rays are shot from the camera through each required pixel of the rendered screen window into the scene. These are called 'primary rays', but sometimes they are referred to as 'eye' or 'camera rays' (Camera (AA) (anti-aliasing)) as they are cast from the rendering view. Sometimes they are called 'pixel samples'.

The Camera (AA) value controls the pixel supersampling rate or the number of rays per pixel that will be traced from the camera. The higher the number of samples, the better the anti-aliasing quality, but the longer the render times.

Note that this process is not linear, as, for each of these sampling rates, the actual number of samples taken is the square of the input value. For example, if Camera (AA) samples is 3, it means that 3x3 = 9 samples will be used for anti-aliasing. If diffuse samples is 2, then 2x2 = 4 samples will be used for the Diffuse GI. The same applies to the other values.

These hen the source of noise is identified in the scene, it is more efficient to set the sampling values to increase the number of only those specific rays. If for example, there is a scene with lots of motion blur, a larger Camera (AA) samples could be described as primary rays (or pixel samples) and determine the overall quality of the image being rendered. Increasing the Camera (AA) samples improves the overall quality of the image, but it can often be wasteful because it increases the sampling rate for everything. W Camera (AA) sample is required, and therefore the other sample values can be reduced. Likewise, increasing Camera (AA) can also benefit indirect lighting, and therefore not as many diffuse samples would be required. However, if you were to reduce noise on the skin of a character, it would be more efficient to have higher SSS samples and not such a high value for Camera (AA) samples.

Light Sampling

Direct lighting rays can be described as rays which deal with lights. These rays travel from a position in the scene toward the various light sources. These rays determine if a surface is in shadow, and if not, lighting information can be calculated.

Noise from lights can sometimes be difficult to diagnose, particularly if it is a light with a large area or size. In these cases, it can sometimes be mistaken for indirect diffuse noise. This highlights the necessity for testing different noise ray types. If the issue is shadow noise, then we can simply toggle ignore shadows in the Arnold render settings, and the noise will completely resolve. The images below show how a light is traced in Arnold.

The same noise problems described earlier can occur with direct and indirect rays. Noise from direct light sources usually appears in specular highlights or in large, soft shadows from area lights. If this is the case, the number of light samples needs to be increased. The images below show the difference in the shadow noise when increasing the number of light samples from 1 to 3.

It can be useful to separate one source of noise from another when trying to evaluate noise in a scene. Disabling diffuse rays (0) can help identify which type of noise is present. When attempting to optimize the number of indirect diffuse rays in a scene, rather than increasing the number of diffuse rays (render time will double for each diffuse sample), the source of the noise will need to be isolated first.

Diffuse Ray Sampling

Indirect (diffuse) lighting from emissive green cube. Rollover image to view direct lighting only (diffuse samples: 0)

Indirect diffuse rays are rays that interact with objects and their surface shaders. Therefore, rays travel in the scene in directions determined by the shader assigned to the object. Transmission rays travel through objects. When a ray hits a reflective object, such as a mirror, only one reflection ray is traced from that point in a direction determined by the incoming ray. In contrast, diffuse rays are sampled randomly over the hemisphere around the hit point.

Diagram showing how diffuse rays are propagated in an Arnold render

Specular Ray Sampling

When rendering glossy specular surfaces, noise can also be a problem, as with diffuse rays. Bright hotspots can cause noise in indirect specular samples. For example, wide specular reflections of small, bright lights. If the issue is noise in a specular highlight, it needs to be confirmed that the source is the direct light and not a secondary ray type (such as specular). This is easy to achieve by setting the GI_diffuse_depth, GI_specular_depth to zero (this essentially turns off all global illumination). If the noise is still there, we know it is the direct specular component of the illumination model. In most cases, it can be resolved by increasing the number of specular samples.

Step Size

Volume ray depth

Increasing the volume_ray_depth can make a dramatic difference to the appearance of a volume. However, be aware that increasing the volume ray depth will increase the number of multiple scattering bounces within the volume (defaults to 0), and therefore render times will increase significantly.

Further information about sampling can be found here.

Further information about removing noise can be found here.

Pepe model by Daniel M. Lara (Pepeland).

# data[].attributes.attachment_link.description
When working with a renderer like Arnold, it is useful to have a basic understanding of the core principles behind ray-trace rendering. Producing a realistic-looking image of a virtual scene requires simulating the propagation of light in the scene all the way from the light sources to the camera.

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Comparing Blender Render with and without OptiX Denoiser 

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Comparing Blender Render with and without OptiX Denoiser 

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https://www.youtube.com/watch?v=eGAjsSNtX6E

Key notes:
- Optix uses less samples but produces the result way faster better compared to blender's render.
-What Blender can produce with 20,000 samples; Optix can achieve with just 200.
-Might not give the best result for animations since the sample generated aren't consistent thus despite not looking grainy, the scene would have an odd filter to it whenever something moves in the scene.

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Reducing render times by 92%! Denoiser showdown

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How long does it take to render a scene without a denoiser? 

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How long does it take to render a scene without a denoiser? 

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https://knowledge.autodesk.com/support/3ds-max/troubleshooting/caas/sfdcarticles/sfdcarticles/Single-high-resolution-frame-with-Arnold-CPU-takes-a-long-time-to-render-in-3ds-Max.html

When rendering a scene file in 3ds Max with Arnold CPU renderer, the scene takes an extremely long time to complete the Arnold preview pass and final rendered frame when the resolution is higher than 2K.

For example, rendering a 4K image takes up to 12 hours.
So a 2 min render animation would take 12 hours to finish if the resolution is higher than 2K in Maya

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Single, high resolution frame with Arnold CPU takes a long time to render in 3ds Max

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When rendering a scene file in 3ds Max with Arnold CPU renderer, the scene takes an extremely long time to complete the Arnold preview pass and final rendered frame when the resolution is higher than 2K. For example, rendering a 4K image takes up to 12 hours. This issue can be caused by, but is not…

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NIVIDIA Desnoiser used in WatchDogs Legion

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NIVIDIA Desnoiser used in WatchDogs Legion

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https://developer.nvidia.com/blog/nvidia-real-time-denoiser-delivers-best-in-class-denoising-in-watch-dogs-legion/

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Real-time ray tracing is more performant than ever with the release of NVIDIA Real-Time Denoiser (NRD). Available today, NRD is a spatio-temporal API agnostic denoising library that's designed to work with low rpp (ray per pixel) signals, and is the only denoiser variable that works with 0.5 or 1 ray per pixel. It uses input signals and environmental conditions to deliver results comparable to ground truth images.
NRD Raising the Bar in Ubisoft's Watch Dogs: Legion
NRD was used in the production of Ubisoft's Watch Dogs: Legion, just released on PC. "Every developer adding ray tracing to their game needs a denoiser that runs fast and generates an excellent image," saidZurab Abelashvili, 3D Programmer, Ubisoft Kyiv. "We've been really pleased with NVIDIA's solution; it allows us to make the very best of our ray budget, delivering exceptional quality without compromising performance."

The video below shows the raw values returned by the stochastic rays reflecting on physically-based materials. Compare this to the virtually noise-free output from NRD, along with the integration into the final game lighting : You can see the heavy lifting NRD does in real-time to resolve image noise.
50% Performance Over SVGF
NVIDIA'S prior denoising solution for real-time ray tracing - SVGF (Spatiotemporal Variance-Guided Filtering) - was introduced in 2017, and is the foundation for several proprietary denoisers being used today. NRD offers better image quality than SVGF, both when stationary and when the camera is moving. Lighting and shadows in NRD are softer and more realistic, and overall performance is increased by roughly 50% (+48.2% for 1080p, +49% for 1440p, and +51.3% for 4K vs the original SVGF implementation).
NRD supports denoising of three signal types:

Diffuse: Scattered lighting reflected in all directions (with some exceptions can be called "view independent", prevails on dielectric materials). The algorithm uses hit distance to guide the denoising process. This allows developers to denoise ambient occlusion together with diffuse radiance for free.

Specular or Reflections: Lighting reflected in a particular direction or cone (view dependent, prevails on metals). The algorithm uses hit distance to guide the denoising process, it allows to denoise specular occlusion together with specular radiance for free.

Infinite Light Source Shadows: Sun or any other infinite light source visibility information (shadow).

Faster, More Robust, Easy to Use

Fast ray tracing denoising solution

Designed to work with 0.5 or 1 ray per pixel

Integrate easily with DX11, DX12, and Vulkan APIs.

Full source code available

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NVIDIA Real-Time Denoiser Delivers Best-in-Class Denoising in Ubisoft's Watch Dogs Legion | NVIDIA Developer Blog

# data[].attributes.attachment_link.description
Real-time ray tracing is more performant than ever with the release of NVIDIA Real-Time Denoiser (NRD). Available today, NRD is a spatio-temporal API agnostic denoising library that's designed to work with low rpp (ray per pixel) signals, and is the only denoiser variable that works with 0.5 or 1 ray per pixel.

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https://developer.nvidia.com/optix-denoiser

Uses GPU-accelerated artificial intelligence to dramatically reduce the time to render a high fidelity image that is visually noiseless. This provides ultra-fast interactive feedback to artists, allowing them to iterate their creative decisions more quickly and achieve their final product much faster.

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NVIDIA OptiX™ AI-Accelerated Denoiser OptiX 5.0 introduces an AI-accelerated denoiser based on a paper published by NVIDIA research “Interactive Reconstruction of Monte Carlo Image Sequences using a Recurrent Denoising Autoencoder”. It uses GPU-accelerated artificial intelligence to dramatically red…

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Sample of a noisy image and a less noisy image

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Sample of a noisy image and a less noisy image

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Denoising is the process of eliminating as much "Noise" in an image.
"Noise" refers to the grainy effect of an image.
The more "Noisy" an image is, the more grainy it looks which usually means the quality is really bad.
The less "Noisy" an image is, the less grainy it looks which means the quality is very good.

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Lead Question: Can NVIDIA's OptiX AI-Accelerated Denoiser be used in the animation industry as a standard to reduce work timetables?

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Lead Question: Can NVIDIA's OptiX AI-Accelerated Denoiser be used in the animation industry as a standard to reduce work timetables?