Countering Racial Bias in Computer Graphics Research

Resources from ACM SIGGRAPH 2021, 2022, 2023, 2024

   

Current computer graphics research practices contain racial biases that have resulted in algorithms for generating "skin" and "hair" that focus on the hegemonic visual features of Europeans and East Asians. These algorithms are widely viewed as universally applicable to all humans, but their underlying technical formulations specifically excel at generating pale skin and straight hair. Faithfully depicting other human features, such as Black skin or Afro-textured hair, is an ongoing and strikingly neglected scientific research problem.

This is distinct from the workplace diversity problem, where the scientists in the field are demographically homogeneous. This is distinct from the training set problem, where machine learning algorithms are biased because they were trained on biased data.

Instead, this is the problem of cultural assumptions dictating which human features are worthy of scientific inquiry, and which are considered unworthy "edge" cases. These assumptions have now become opaquely codified in the core mathematics of our computer graphics algorithms.

The following are resources that we have assembled since 2020, at SIGGRAPH and beyond, to broaden our horizons. Our goal is to legitimize computer graphics research into algorithms for non-hegemonic human features such as dark skin, highly coiled hair, and non-binary gender.

   
Participants
   
  • Victoria Abrevaya (MPI)
  • Curtis Andrus (Animal Logic)
  • Victor Araujo (PUCRS)
  • Tadas Baltrusaitis (Microsoft)
  • Florence Bertails-Descoubes (INRIA)
  • Michael J. Black (MPI)
  • Timo Bolkart (MPI)
  • Gordon Cameron (Epic Games)
  • Angelo Brandelli Costa (PUCRS)
  • Octave Crespel (INRIA)
  • Mathew Cross (Victoria University of Wellington)
  • A.M. Darke (University of California, Santa Cruz)
  • Ana Dodik (MIT)
  • Julie Dorsey (Yale University)
  • Areito Echevarria (Victoria University of Wellington)
  • Haven Feng (MPI)
  • Jessica Heidt (Pixar)
  • Charlie Hewitt (Microsoft)
  • Emile Hohnadel (INRIA)
  • Alec Jacobson (University of Toronto)
  • Wojciech Jarosz (Dartmouth College)
  • Zichen Jie (Victoria University of Wellington)
  • Paul Kanyuk (Pixar)
  • Mason Khoo (Walt Disney Animation)
  • Theodore Kim (Yale University)
  • Michael Launder (Nickelodeon Animation)
  • Dan Lipson (Walt Disney Animation)
  • Mara MacMahon (Pixar)
  • James Malazita (RPI)
  • Edgar Mallari (Victoria University of Wellington)
  • Thibaut Metivet (INRIA)
  • Joshua Minor (Pixar)
  • Soraia Raupp Musse (PUCRS)
  • Derek Nowrouzezahrai (McGill University)
  • Peter Nye (Pixar)
  • Sofya Ogunseitan (Pixar)
  • Yoehan Oh (Yale University)
  • Isaac Olander (Tallgran)
  • Jarred Parr (Yale University)
  • Lohit Petikam (Microsoft)
  • Amanda Phillips (Georgetown University)
  • Shideh Rezaeifar (Microsoft)
  • Holly Rushmeier (Yale University)
  • Diogo Schaffer (PUCRS)
  • Silvia Sellán (Columbia University)
  • Alvin Shi (Yale University)
  • Soto Solis (Weta Digital)
  • Raqi Syed (Victoria University of Wellington)
  • Joachim Tesch (MPI)
  • Mehau Tikaua-Williams (Victoria University of Wellington)
  • Jacinda Tran (Harvard University)
  • Jose Velasquez (Walt Disney Animation)
  • Marta Wilczkowiak (Microsoft)
  • Emily Wilson (Pixar)
  • Haomiao Wu (Yale University)
   
2020
   
    The Racist Legacy of Computer-Generated Humans.
Theodore Kim
Scientific American 2020.
[Article] [Cached PDF]

   
   
2021
   
    Anti-Racist Graphics Research.
Theodore Kim
SIGGRAPH Diversity Equity & Inclusion Summit 2021.
[YouTube] [Slides]

Many of the basic research problems we take for granted in computer graphics contain insidious assumptions about race. These troubling issues pre-date computer graphics, and can be traced back to the film technology and techniques from the analog era. Far from being incidental, they directly determine the physical formulations and numerical algorithms we use to depict virtual humans today. Instead of perpetuating the prejudices of previous eras, can we engage in anti-racist research that works to dismantle it?

   
   
    Countering Racial Bias in Computer Graphics Research Requires Structural Change
Theodore Kim, Holly Rushmeier, Raqi Syed, Wojciech Jarosz, A.M. Darke
ACM SIGGRAPH Birds of a Feather 2021.
[Slides, Part 1] [Slides, Part 2]

This BOF is for attendees interested in discussing issues of racial bias that have long been embedded in computer graphics research. More than just an issue of workforce diversity, we will discuss discriminatory assumptions embedded in our community's basic technical formulations.

Overcoming these biases will require community-wide structural changes. Research that depicts all forms of humanity must be initiated, but also recognized as valid, non-niche, lines of inquiry. This will be a friendly, collaborative space for mutual, authentic engagement across difference. Attendees can be at any stage, including learning about, taking steps toward, or enacting change in computer graphics research.

   
   
2022
   
    Sex and Gender in the Computer Graphics Research Literature.
Ana Dodik*, Silvia Sellán*, Theodore Kim, and Amanda Phillips (* joint 1st authors)
ACM SIGGRAPH Talks (North America) 2022.
[PDF] [Supplement] [YouTube] [arXiv] [Phillips's Book]

We survey the treatment of sex and gender in the Computer Graphics research literature from an algorithmic fairness perspective. The established practices on the use of gender and sex in our community are scientifically incorrect and constitute a form of algorithmic bias with potential harmful effects. We propose ways of addressing these trends as technical limitations.

   
   
    Space Rangers With Cornrows
Sofya Ogunseitan

ACM SIGGRAPH Talks (North America) 2022.
[PDF]

This presentation is a debrief of the processes and methods added to Pixar's groom pipeline to create the hairstyles of Lightyear characters Alisha and Izzy Hawthorne. The processes include novel ways of generating braids, curls, braid partitioning hairs (edge hairs), and graphic shapes populated with hair.

   
   
    Countering Racial Bias in Computer Graphics Research.
Theodore Kim, Holly Rushmeier, Julie Dorsey, Derek Nowrouzezahrai, Raqi Syed, Wojciech Jarosz, and A.M. Darke
ACM SIGGRAPH Talks (North America) 2022.
[PDF] [Supplement] [arXiv] [Adobe Lecture] [Slides]

   
   
    On Fairness in Face Albedo Estimation
Haven Feng, Timo Bolkart, Joachim Tesch, Michael J. Black, Victoria Abrevaya
ACM SIGGRAPH Talks (North America) 2022.
[PDF] [ACM DL]

Digital avatars will be crucial components for immersive telecommunication, gaming, and the coming metaverse. Unfortunately, current methods for estimating the facial appearance (albedo) are biased to estimate light skin tones. This talk raises awareness of the problem with an analysis of (1) dataset biases and (2) the light/albedo ambiguity. We show how these problems can be ameliorated by recent advances, improving fairness in albedo estimation.

   
   
    Using STS to Bridge Long Histories of Blackness, Specularity, and Rendering
James Malazita
ACM SIGGRAPH Talks (North America) 2022.
[PDF] [YouTube] [ACM DL] [Malazita's Book]

Science and Technology Studies (STS) is an academic interdisicpline that uses sociological and historical methods to study the interrelations of society and technoscience. This paper uses an STS approach to examine the historical feedback loops between "rendering" the shine and specularity of Black skin - across painting, video, and photography - and how computer graphics programmers and artists should question some of the fundamental assumptions of their rendering workflows to both create more equitable representation of human form, and also to understand how computational renderings influence the real world they represent.

   
   
    Visual Effects Pedagogy: Diversity, Equity, and Inclusion as Visible and Invisible Attributes
Raqi Syed, Areito Echevarria, Edgar Mallari, Mehau Tikaua-Williams, Soto Solis, Mathew Cross, Zichen Jie
ACM SIGGRAPH Talks (North America) 2022.
[PDF] [ACM DL]

Due to our proximity to industry pathways, VFX curriculums are good at mapping visible graduate attributes to core skills. Visible attributes are skills that can be measured via portfolio work and are reflected on student transcripts. Examples of such attributes may be building digital humans, creating physically accurate shaders, and designing story worlds. However, in order for the discipline of VFX to reflect our dynamic global culture and ensure equitable workplaces, we must also find ways to map graduate attributes to the values that drive technical and cultural diversity. Such attributes are harder to measure and can be understood as invisible attributes.

   
   
    Tracking Character Diversity in the Animation Pipeline
Mara MacMahon, Emily Wilson, Peter Nye, Gordon Cameron, Jessica Heidt, Joshua Minor, Paul Kanyuk
ACM SIGGRAPH Talks (North America) 2022.
[PDF]

As we explore a broad range of characters and stories in our films, it has become increasingly valuable to view breakdowns of our character pools and selections by demographic: to build and use our assets efficiently, reinforce storytelling and world building choices, and ensure consistent decision-making across the pipeline. With the Character Linker App within Traction (Traction is Pixar's asset and shot-tracking tool), production is able to see a live breakdown of the character pool as assets are built, and sequence/shot composition, as they are populated with the ability to visualize by a range of categories, including gender, ethnicity, body-type, and age, among others. Each film can define and populate these categories specific to their story, set breakdown goals to measure progress against, and iterate on crowd asset selections to ensure each character is utilized to the fullest.

   
   
    Inclusive Character Creator: A Showcase of Inclusive Design for 3D Character Creators
Michelle Ma
ACM SIGGRAPH Posters (North America) 2022.
[Project]

Inclusive Character Creator is a speculative design research project that seeks to address some of the long-standing issues of sexism, racism, ableism, and sizeism prevalent in most 3D character creators in interactive media. This project focuses on stylized and expressive features rather than hyperrealism. It seeks to redefine what it means to start a character from a "default body," a definition that usually results in creating a biased system that relies on media norms. A version 1.0 has been built, encapsulating fundamental principles resulting from research.

   
   
    Towards Virtual Humans without Gender Stereotyped Visual Features
Victor Araujo, Diogo Schaffer, Angelo Brandelli Costa, Soraia Raupp Musse
ACM SIGGRAPH Asia Technical Briefs 2022.
[PDF] [ACM DL]

Animations have become increasingly realistic with the evolution of Computer Graphics (CG). In particular, human models and behaviors have been represented through animated virtual humans. Gender is a characteristic related to human identification, so virtual humans assigned to a specific gender have, in general, stereotyped representations through movements, clothes, hair, and colors in order to be understood by users as desired by designers. An important area of study is determining whether participants' perceptions change depending on how a virtual human is visually presented. Findings in this area can help the industry guide the modeling and animation of virtual humans to deliver the expected impact to the public. In this paper, we reproduce using an animated CG baby, a previous perceptual study conducted in real life aimed to assess gender bias about a baby. Our research indicates that simply textually reporting a virtual human's gender may be sufficient to create a perception of gender that affects the participant's emotional response so that stereotyped behaviors can be avoided.

   
   
    Countering Racial Bias in Computer Graphics Research (the BOF): One Year Later
Theodore Kim, Holly Rushmeier, Raqi Syed, Derek Nowrouzezahrai
ACM SIGGRAPH Birds of a Feather 2022.
[Slides, Part 1] [Slides, Part 2]

This BOF is for attendees interested in discussing issues of racial bias embedded in computer graphics research. It is a follow-on from last year's BOF, "Countering Racial Bias in Computer Graphics Research Requires Structural Change", as well as this year's Talk, "Countering Racial Bias in Computer Graphics Research".

We will celebrate progress over the last year, discuss setbacks, and brainstorm paths forward. This will be a friendly, collaborative space for mutual, authentic engagement across difference. Attendees can be at any stage, including learning about, taking steps toward, or enacting change in computer graphics research.

   
   
2023
   
    Lifted Curls: A Model For Tightly Coiled Hair Simulation.
Alvin Shi*, Haomiao Wu*, Jarred Parr, A.M. Darke and Theodore Kim (* joint 1st authors)
Symposium on Computer Animation (SCA) 2023.
[PDF] [Project] [YouTube] [Supplement] [Matlab/Octave Source]

We present an isotropic, hyperelastic model specifically designed for the efficient simulation of tightly coiled hairs whose curl radii approach 5 mm. Our model is robust to large bends and torsions, even when they appear at the scale of the strand discretization. The terms of our model are consistently quadratic with respect to their primary variables, do not require per-edge frames or any parallel transport operators, and can efficiently take large timesteps on the order of 1/30 of a second. Additionally, we show that it is possible to obtain fast, closed-form eigensystems for all the terms in the energy. Our eigenanalysis is sufficiently generic that it generalizes to other models. Our entirely vertex-based formulation integrates naturally with existing finite element codes, and we demonstrate its efficiency and robustness in a variety of scenarios.

   
   
    Lighting and Look Dev for Skin Tones in Disney's "Strange World"
Mason Khoo, Dan Lipson, Jose Velasquez
DigiPro 2023.
[ACM DL]

Artists at Walt Disney Animation Studios have been constantly seeking to improve the physical depiction of an increasingly wider range of skin tones with each subsequent film. "Strange World" presented a great opportunity to improve on how we portray a wide range of skin types. The changes we implemented included: creating a new skin material from the ground up, changing the testing light rig to better evaluate materials, and implementing lighting strategies to better represent the skin properties of each character. What resulted was character skin that improved on our depiction of a wider range of skin types while maintaining a level of stylization in line with the art direction of the film.

   
   
2024
   
    Gender Diversity of Graphics Conference Leadership
Alec Jacobson
ACM SIGGRAPH Talks (North America) 2024.

In our analysis of gender diversity in graphics conference leadership, we examined the underrepresentation of non-male researchers, including women and non-binary individuals, in high-profile roles across key conferences from 2010 to 2023. Our study focused on Conference Chair, Papers Chair, and Keynote Speaker positions at six major conferences. Using perceived gender based on pronouns, we found 19% non-male representation among 543 leadership positions, with SIGGRAPH North America showing higher non-male participation. Our data also revealed a limited leadership circle with repeated roles filled by a small number of women, indicating a potential "diversity tax." We observed a trend of increasing non-male representation over time, though the pace is uncertain. Furthermore, our study suggests a correlation between the gender of conference chairs and keynote speakers, underscoring the importance of diverse leadership. We conclude that increasing non-male and particularly non-binary representation is crucial for reflecting societal and student demographics, yet we emphasize the need for a broader approach to address representational diversity and inclusivity in the graphics community.

   
   
    Monsters, Family, and Shenanigans, OH MY! Our CG Approach to Representation at Nickelodeon Animation
Samuel Hale, Areeba Khan, Michael Launder, Rommel Calderon, Leslie Wishnevski
ACM SIGGRAPH Production Sessions 2024.
[ACM DL]

Telling amazing stories involving beloved characters is at the forefront of what we do at Nickelodeon Animation Studio. It is imperative to tell these stories with characters from diverse backgrounds and experiences, as it is important to see the world through their eyes and perspective. We pride ourselves in our history of demonstrating diversity, equity, and inclusion in our shows, and continue to innovate our CG processes and workflows to keep DEI representation relevant in the broadcast space. Recent productions such as "Big Nate", "Transformers: EarthSpark", and "Monster High" exhibit our commitment to DEI. This panel will demonstrate the efforts, focus, and resoluteness we pursue on being inclusive and authentically representing our characters in our productions.

   
   
    Contact Detection Between Curved Fibres: High Order Makes a Difference
Octave Crespel, Emile Hohnadel, Thibaut Metivet, Florence Bertails-Descoubes
ACM Transactions on Graphics 2024.
[PDF] [Project] [ACM DL]

Computer Graphics has a long history in the design of effective algorithms for handling contact and friction between solid objects. For the sake of simplicity and versatility, most methods rely on low-order primitives such as line segments or triangles, both for the detection and the response stages. In this paper we carefully analyse, in the case of fibre systems, the impact of such choices on the retrieved contact forces. We highlight the presence of artifacts in the force response that are tightly related to the low-order geometry used for contact detection. Our analysis draws upon thorough comparisons between the high-order super-helix model and the low-order discrete elastic rod model. These reveal that when coupled to a low-order, segment-based detection scheme, both models yield spurious jumps in the contact force profile. Moreover, these artifacts are shown to be all the more visible as the geometry of fibres at contact is curved. In order to remove such artifacts we develop an accurate high-order detection scheme between two smooth curves, which relies on an efficient adaptive pruning strategy. We use this algorithm to detect contact between super-helices at high precision, allowing us to recover, in the range of wavy to highly curly fibres, much smoother force profiles during sliding motion than with a classical segment-based strategy. Furthermore, we show that our approach offers better scaling properties in terms of efficiency vs. precision compared to segment-based approaches, making it attractive for applications where accurate and reliable forces are desired. Finally, we demonstrate the robustness and accuracy of our fully high-order approach on a challenging hair combing scenario.

   
   
    The Life and Legacy of Búi Tướng-Phong.
Yoehan Oh, Jacinda Tran, and Theodore Kim
ACM SIGGRAPH Talks (North America) 2024.
[PDF] [arXiv] [TIME Article]

We examine the life and legacy of pioneering Vietnamese computer scientist Búi Tướng Phong, whose shading and lighting models turned 50 last year. We trace the trajectory of his life through Vietnam, France, and the United States, and its intersections with global conflicts. Crucially, we present definitive evidence that his name has been cited incorrectly over the last five decades. His family name is Búi Tướng, not Phong. By presenting these facts at SIGGRAPH, we hope to collect more information about his life, and ensure that his name is remembered correctly in the future.

   
   
    More Than Killmonger Locs: A Style Guide for Black Hair (in Computer Graphics)
A.M. Darke, Isaac Olander, Theodore Kim
ACM SIGGRAPH Course 2024.
[Darke's Slides] [Kim's Slides] [Code My Crown] [OSAHL]

We will cover recent advances and ongoing challenges in the depiction of Black hair, otherwise known as kinky, or Afro-textured hair. In computer graphics, the majority hair research has been in the depiction straight or wavy hair. As a result, many aspects of the aesthetics and mechanics of Black hair remain poorly understood. To help fill this gap, we will present Code My Crown, a free guide to creating Black digital hairstyles that we co-authored in collaboration with a community of game artists and Dove. We also cover styling guidelines for 3D models in the Open Source Afro Hair Library, and present Lifted Curls, our strand simulation technique specifically designed for Afro-textured hair. Finally, we will suggest future directions for hair research.

   
   
    Scribble: Auto-generated 2D avatars with diverse and inclusive art direction
Lohit Petikam, Charlie Hewitt, Shideh Rezaeifar
ACM SIGGRAPH Posters (North America) 2024.
[PDF] [ACM DL]

Stylized avatars used in hybrid telepresence must support the large diversity in human appearance existing in the world. Most avatar systems assume a generic base rig that morphs into varied face and body shapes. However, retrofitting shapes for under-represented populations as an afterthought is costly. We need new avatar systems, visual languages, and human understanding technology, all co-designed with diversity in mind from the start.

   
   
    Countering Racial Bias in Computer Graphics Research: Three Years Later
Theodore Kim, A.M. Darke, Alec Jacobson, Lohit Petikam, Curtis Andrus, Holly Rushmeier, Wojciech Jarosz
ACM SIGGRAPH Birds of a Feather 2024.
[Slides, Part 1] [Slides, Part 2] [Petikam's Slides]

This BOF is for attendees interested in discussing issues of racial bias embedded in computer graphics research. It is a follow-on from the SIGGRAPH 2021 BOF, "Countering Racial Bias in Computer Graphics Research Requires Structural Change", as well as the SIGGRAPH 2022 Talk and BOF, "Countering Racial Bias in Computer Graphics Research". We will celebrate progress over the last three years, discuss setbacks, and brainstorm paths forward. This will be a friendly, collaborative space for mutual, authentic engagement across difference. Attendees can be at any stage, including learning about, taking steps toward, or enacting change in computer graphics research.

   
   
Talks on YouTube