Saliency in VR: How do people explore virtual environments? - Vincent Sitzmann; Ana Serrano; Amy Pavel; Maneesh Agrawala; Diego Gutierrez; Gordon Wetzstein (CoRR, 2016)

Dirty Pixels: Optimizing Image Classification Architectures for Raw Sensor Data. - Steven Diamond; Vincent Sitzmann; Stephen P. Boyd; Gordon Wetzstein; Felix Heide (CoRR, 2017)

Unrolled Optimization with Deep Priors. - Steven Diamond; Vincent Sitzmann; Felix Heide; Gordon Wetzstein (CoRR, 2017)

Movie editing and cognitive event segmentation in virtual reality video. - Ana Serrano; Vincent Sitzmann; Jaime Ruiz-Borau; Gordon Wetzstein; Diego Gutierrez; Belén Masiá (ACM Trans. Graph., 2017)

End-to-end optimization of optics and image processing for achromatic extended depth of field and super-resolution imaging. - Vincent Sitzmann; Steven Diamond; Yifan Peng 001; Xiong Dun; Stephen P. Boyd; Wolfgang Heidrich; Felix Heide; Gordon Wetzstein (ACM Trans. Graph., 2018)

Towards a Machine-Learning Approach for Sickness Prediction in 360° Stereoscopic Videos. - Nitish Padmanaban; Timon Ruban; Vincent Sitzmann; Anthony M. Norcia; Gordon Wetzstein (IEEE Trans. Vis. Comput. Graph., 2018)

Saliency in VR: How Do People Explore Virtual Environments? - Vincent Sitzmann; Ana Serrano; Amy Pavel; Maneesh Agrawala; Diego Gutierrez; Belén Masiá; Gordon Wetzstein (IEEE Trans. Vis. Comput. Graph., 2018)

DeepVoxels: Learning Persistent 3D Feature Embeddings. - Vincent Sitzmann; Justus Thies; Felix Heide; Matthias Nießner; Gordon Wetzstein; Michael Zollhöfer (CVPR, 2019)

Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations. - Vincent Sitzmann; Michael Zollhöfer; Gordon Wetzstein (NeurIPS, 2019)

Semantic Implicit Neural Scene Representations With Semi-Supervised Training. - Amit Pal Singh Kohli; Vincent Sitzmann; Gordon Wetzstein (3DV, 2020)

MetaSDF: Meta-Learning Signed Distance Functions. - Vincent Sitzmann; Eric R. Chan; Richard Tucker 001; Noah Snavely; Gordon Wetzstein (NeurIPS, 2020)

Implicit Neural Representations with Periodic Activation Functions. - Vincent Sitzmann; Julien N. P. Martel; Alexander W. Bergman; David B. Lindell; Gordon Wetzstein (NeurIPS, 2020)

State of the Art on Neural Rendering. - Ayush Tewari; Ohad Fried; Justus Thies; Vincent Sitzmann; Stephen Lombardi; Kalyan Sunkavalli; Ricardo Martin-Brualla; Tomas Simon; Jason M. Saragih; Matthias Nießner; Rohit Pandey; Sean Ryan Fanello; et al. (Comput. Graph. Forum, 2020)

Inferring Semantic Information with 3D Neural Scene Representations. - Amit P. S. Kohli; Vincent Sitzmann; Gordon Wetzstein (CoRR, 2020)

3D Neural Scene Representations for Visuomotor Control. - Yunzhu Li; Shuang Li 013; Vincent Sitzmann; Pulkit Agrawal 001; Antonio Torralba 001 (CoRL, 2021)

Single-Shot Scene Reconstruction. - Sergey Zakharov; Rares Andrei Ambrus; Vitor Guizilini; Dennis Park; Wadim Kehl; Frédo Durand; Joshua B. Tenenbaum; Vincent Sitzmann; Jiajun Wu 001; Adrien Gaidon (CoRL, 2021)

Learning Signal-Agnostic Manifolds of Neural Fields. - Yilun Du; Katie Collins; Josh Tenenbaum 001; Vincent Sitzmann (NeurIPS, 2021)

Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering. - Vincent Sitzmann; Semon Rezchikov; Bill Freeman; Josh Tenenbaum 001; Frédo Durand (NeurIPS, 2021)

Advances in neural rendering. - Ayush Tewari; Ohad Fried; Justus Thies; Vincent Sitzmann; Stephen Lombardi; Zexiang Xu; Tomas Simon; Matthias Nießner; Edgar Tretschk; Lingjie Liu; Ben Mildenhall; Pratul P. Srinivasan; et al. (SIGGRAPH Courses, 2021)

Deep Medial Fields. - Daniel Rebain; Ke Li 011; Vincent Sitzmann; Soroosh Yazdani; Kwang Moo Yi; Andrea Tagliasacchi (CoRR, 2021)

Dirty Pixels: Towards End-to-end Image Processing and Perception. - Steven Diamond; Vincent Sitzmann; Frank D. Julca-Aguilar; Stephen P. Boyd; Gordon Wetzstein; Felix Heide (ACM Trans. Graph., 2021)

Kubric: A scalable dataset generator. - Klaus Greff; Francois Belletti; Lucas Beyer; Carl Doersch; Yilun Du; Daniel Duckworth; David J. Fleet; Dan Gnanapragasam; Florian Golemo; Charles Herrmann; Thomas Kipf; Abhijit Kundu; et al. (CVPR, 2022)

Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. - Anthony Simeonov; Yilun Du; Andrea Tagliasacchi; Joshua B. Tenenbaum; Alberto Rodriguez 003; Pulkit Agrawal 001; Vincent Sitzmann (ICRA, 2022)

Decomposing NeRF for Editing via Feature Field Distillation. - Sosuke Kobayashi; Eiichi Matsumoto; Vincent Sitzmann (NeurIPS, 2022)

Advances in Neural Rendering. - Ayush Tewari; Justus Thies; Ben Mildenhall; Pratul P. Srinivasan; Edgar Tretschk; Yifan Wang 011; Christoph Lassner; Vincent Sitzmann; Ricardo Martin-Brualla; Stephen Lombardi; Tomas Simon; Christian Theobalt; et al. (Comput. Graph. Forum, 2022)

Neural Fields in Visual Computing and Beyond. - Yiheng Xie; Towaki Takikawa; Shunsuke Saito; Or Litany; Shiqin Yan; Numair Khan; Federico Tombari; James Tompkin 001; Vincent Sitzmann; Srinath Sridhar 002 (Comput. Graph. Forum, 2022)

Seeing 3D Objects in a Single Image via Self-Supervised Static-Dynamic Disentanglement. - Prafull Sharma; Ayush Tewari; Yilun Du; Sergey Zakharov; Rares Ambrus; Adrien Gaidon; William T. Freeman; Frédo Durand; Joshua B. Tenenbaum; Vincent Sitzmann (CoRR, 2022)

Learning to Render Novel Views from Wide-Baseline Stereo Pairs. - Yilun Du; Cameron Smith; Ayush Tewari; Vincent Sitzmann (CVPR, 2023)

DeLiRa: Self-Supervised Depth, Light, and Radiance Fields. - Vitor Guizilini; Igor Vasiljevic; Jiading Fang; Rares Ambrus; Sergey Zakharov; Vincent Sitzmann; Adrien Gaidon (ICCV, 2023)

Neural Groundplans: Persistent Neural Scene Representations from a Single Image. - Prafull Sharma; Ayush Tewari; Yilun Du; Sergey Zakharov; Rares Andrei Ambrus; Adrien Gaidon; William T. Freeman; Frédo Durand; Joshua B. Tenenbaum; Vincent Sitzmann (ICLR, 2023)

FlowCam: Training Generalizable 3D Radiance Fields without Camera Poses via Pixel-Aligned Scene Flow. - Cameron Smith; Yilun Du; Ayush Tewari; Vincent Sitzmann (NeurIPS, 2023)

Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision. - Ayush Tewari; Tianwei Yin; George Cazenavette; Semon Rezchikov; Josh Tenenbaum 001; Frédo Durand; Bill Freeman; Vincent Sitzmann (NeurIPS, 2023)

Neural Fields for Visual Computing: SIGGRAPH 2023 Course. - Towaki Takikawa; Shunsuke Saito; James Tompkin 001; Vincent Sitzmann; Srinath Sridhar 002; Or Litany; Alex Yu (SIGGRAPH Courses, 2023)

Approaching human 3D shape perception with neurally mappable models. - Thomas P. O'Connell; Tyler Bonnen; Yoni Friedman; Ayush Tewari; Joshua B. Tenenbaum; Vincent Sitzmann; Nancy Kanwisher (CoRR, 2023)

Intrinsic Image Diffusion for Single-view Material Estimation. - Peter Kocsis 001; Vincent Sitzmann; Matthias Nießner (CoRR, 2023)

pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction. - David Charatan; Sizhe Li; Andrea Tagliasacchi; Vincent Sitzmann (CoRR, 2023)

Unsupervised Discovery and Composition of Object Light Fields. - Cameron Smith; Hong-Xing Yu; Sergey Zakharov; Frédo Durand; Joshua B. Tenenbaum; Jiajun Wu 001; Vincent Sitzmann (Trans. Mach. Learn. Res., 2023)

Variational Barycentric Coordinates. - Ana Dodik; Oded Stein; Vincent Sitzmann; Justin Solomon 001 (ACM Trans. Graph., 2023)

Intrinsic Image Diffusion for Indoor Single-view Material Estimation. - Peter Kocsis 001; Vincent Sitzmann; Matthias Nießner (CVPR, 2024)

PixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstruction. - David Charatan; Sizhe Lester Li; Andrea Tagliasacchi; Vincent Sitzmann (CVPR, 2024)

DittoGym: Learning to Control Soft Shape-Shifting Robots. - Suning Huang; Boyuan Chen 003; Huazhe Xu; Vincent Sitzmann (ICLR, 2024)

Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion. - Boyuan Chen 003; Diego Marti Monso; Yilun Du; Max Simchowitz; Russ Tedrake; Vincent Sitzmann (NeurIPS, 2024)

Score Distillation via Reparametrized DDIM. - Artem Lukoianov; Haitz Sáez de Ocáriz Borde; Kristjan H. Greenewald; Vitor Guizilini; Timur M. Bagautdinov; Vincent Sitzmann; Justin M. Solomon (NeurIPS, 2024)

Neural Isometries: Taming Transformations for Equivariant ML. - Thomas W. Mitchel; Michael J. Taylor; Vincent Sitzmann (NeurIPS, 2024)

Robust Biharmonic Skinning Using Geometric Fields. - Ana Dodik; Vincent Sitzmann; Justin Solomon 001; Oded Stein (CoRR, 2024)

Unifying 3D Representation and Control of Diverse Robots with a Single Camera. - Sizhe Lester Li; Annan Zhang; Boyuan Chen 003; Hanna Matusik; Chao Liu 021; Daniela Rus; Vincent Sitzmann (CoRR, 2024)

FlowMap: High-Quality Camera Poses, Intrinsics, and Depth via Gradient Descent. - Cameron Smith; David Charatan; Ayush Tewari; Vincent Sitzmann (3DV, 2025)

History-Guided Video Diffusion. - Kiwhan Song; Boyuan Chen 003; Max Simchowitz; Yilun Du; Russ Tedrake; Vincent Sitzmann (CoRR, 2025)

Snapmoji: Instant Generation of Animatable Dual-Stylized Avatars. - Eric M. Chen; Di Liu 003; Sizhuo Ma; Michael Vasilkovsky; Bing Zhou; Qiang Gao; Wenzhou Wang; Jiahao Luo; Dimitris N. Metaxas; Vincent Sitzmann; Jian Wang (CoRR, 2025)

Controlling diverse robots by inferring Jacobian fields with deep networks. - Sizhe Lester Li; Annan Zhang; Boyuan Chen 003; Hanna Matusik; Chao Liu 021; Daniela Rus; Vincent Sitzmann (Nat., 2025)

Meschers: Geometry Processing of Impossible Objects. - Ana Dodik; Isabella Yu; Kartik Chandra; Jonathan Ragan-Kelley; Joshua B. Tenenbaum; Vincent Sitzmann; Justin Solomon 001 (ACM Trans. Graph., 2025)