Adobe Research at SIGGRAPH 2021

August 9, 2021

Tags: AI & Machine Learning, Computer Vision, Imaging & Video, Conferences, Graphics (2D & 3D)

In this SIGGRAPH 2021 paperresearchers demonstrate a method for manipulating parametric 3D shapes directly, such as putting toast in a toaster or changing the overall structure, without setting manually their parameters.

Adobe has made significant contributions to ACM’s SIGGRAPH 2021 conference, the premier academic conference in computer graphics and interactive techniques. This year, Adobe is proud to have co-authored 13 technical papers, as well as Transactions on Graphics paper that will be presented at the conference.  Adobe authors are also co-organizing a course and presenting one Talk.  Moreover, two of Adobe’s frequent collaborators, Jonathan Ragan-Kelley and Minchen Li, received major awards this year at the conference. Both Ragan-Kelley and Li are being honored for research achievements emerging from intern and collaborative projects with Adobe researchers.  

Adobe researchers will perform significant service and leadership roles at SIGGRAPH this year, including the conference’s Technical Papers Program Chair, Sylvain Paris. Three other Adobe researchers served on the technical papers committee (including one as sorter and advisory board member), another on the steering committee, as well as co-organizers of the theses Fast Forwards and the conference coffee program.

Nearly all of Adobe’s papers are the results of student internships or other collaborations with university students and faculty. Check out the Adobe Research internships and full-time careers pages to learn more about internships and full-time career opportunities.

Here are Adobe’s contributions to SIGGRAPH 2021. 

Technical Papers 

Boundary-Sampled Halfspaces: A New Representation for Constructive Solid Modeling 
Xingyi Du, Qingnan Zhou, Nathan Carr, Tao Ju 
Codimensional Incremental Potential Contact 
Minchen Li, Danny Kaufman, Chenfanfu Jiang 
DAG Amendment for Inverse Control of Parametric Shapes 
Elie Michel, Tamy Boubekeur 
Fast Median Filters using Separable Sorting Networks 
Andrew Adams 
Guaranteed Globally Injective 3D Deformation Processing 
Yu Fang, Minchen Li, Chenfanfu Jiang, Danny Kaufman 
Hierarchical Neural Reconstruction for Path Guiding Using Hybrid Path and Photon Samples 
Shilin Zhu Zexiang Xu, Tiancheng Sun, Alexandr Kuznetsov, Mark Meyer, Henrik Wann Jensen, Hao Su, Ravi Ramamoorthi 
Interactive Monte Carlo Denoising using Affinity of Neural Features 
Mustafa Isik, Krishna Mullia, Matthew Fisher, Jonathan Eisenmann, Michael Gharbi 
Intersection-free Rigid Body Dynamics 
Zachary Ferguson, Minchen Li, Teseo Schneider, Francisca Gil-Ureta, Timothy Langlois, Chenfanfu Jiang, Denis Zorin, Danny Kaufman, Daniele Panozzo 
Medial IPC: Accelerated Incremental Potential Contact with Medial Elastics 
Lei Lan, Yin Yang, Danny Kaufman, Junfeng Yao, Minchen Li, Chenfanfu Jiang 
NeuMIP: Multi-Resolution Neural Materials 
Alexandr Kuznetsov Krishna Mullia, Zexiang Xu, Milos Hasan, Ravi Ramamoorthi 
Neural Complex Luminaires: Representation and Rendering 
Junqiu Zhu, Yaoyi Bai, Zilin Xu, Steve Bako, Edgar Velázquez-Armendáriz, Lu Wang, Pradeep Sen, Miloš Hašan, Ling-Qi Yan 
ShapeMOD: Macro Operation Discovery for 3D Shape Programs 
R. Kenny Jones, David Charatan, Paul Guerrero, Niloy Mitra, Daniel Ritchie  
Swept Volumes via Spacetime Numerical Continuation 
Silvia Sellan, Noam Aigerman, Alec Jacobson 

ToG Paper

StyleFlow: Attribute-conditioned Exploration of StyleGAN-generated Images Using Conditional Continuous Normalizing Flows 
Rameen Abdal, Peihao Zhu, Niloy Mitra, Peter Wonka 


Unbiased Emission and Scattering Importance Sampling For Heterogeneous Volumes 
Wei-Feng, Wayne Huang, Peter Kutz, Yining Karl Li, Matt Jen-Yuan Chiang 


Advances in Neural Rendering (2 sessions: Part 1Part 2) 
Ayush Tewari, Ohad Fried, Justus Thies, Vincent Sitzmann, Stephen Lombardi, Zexiang Xu, Tomas Simon, Matthias Niessner, Edgar Tretschk, Lingjie Liu, Ben Mindenhall, Pratul Srinivasan, Rohit Pandey, Sergio Orts-Escolano, Sean Fanello, Michelle Guo, Gordon Wetzstein, Jun-Yan Zhu, Christian Theobalt, Maneesh Agrawala, Dan Goldman, Michael Zollhoefer 

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