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
Talk
Unbiased Emission and Scattering Importance Sampling For Heterogeneous Volumes Wei-Feng, Wayne Huang, Peter Kutz, Yining Karl Li, Matt Jen-Yuan Chiang
Courses
Advances in Neural Rendering (2 sessions: Part 1; Part 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
