I am an Assistant Professor at MIT EECS, where I am leading the Scene Representation Group. Previously, I did my Ph.D. at Stanford University as well as a Postdoc at MIT CSAIL. My research interest lies in neural scene representations - the way neural networks learn to represent information on our world. My goal is to allow independent agents to reason about our world given visual observations, such as inferring a complete model of a scene with information on geometry, material, lighting etc. from only few observations, a task that is simple for humans, but currently impossible for AI.

Looking for graduate students!

I am looking for graduate students to join my lab at MIT in July 2023. If you want to push what's possible with neural scene representations, inverse graphics and neural rendering and apply them to problems across computer vision, graphics, and robotics, please apply here - deadline is December 15th 2022!


Seeing 3D Objects in a Single Image via Self-Supervised Static-Dynamic Disentanglement
arXiv 2022
Prafull Sharma, Ayush Tewari, Yilun Du, Sergey Zakharov, Rares Ambrus, Adrien Gaidon, William T. Freeman, Fredo Durand, Joshua B. Tenenbaum, Vincent Sitzmann
Decomposing NeRF for Editing via Feature Field Distillation
arXiv 2022
Sosuke Kobayashi, Eiichi Matsumoto, Vincent Sitzmann
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation
arXiv 2021
Anthony Simeonov*, Yilun Du*, Andrea Tagliasacchi, Alberto Rodriguez, Pulkit Agrawal†, Vincent Sitzmann†
Learning Signal-Agnostic Manifolds of Neural Fields
NeurIPS 2021
Yilun Du, Katherine M. Collins, Joshua Tenenbaum, Vincent Sitzmann
Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering
NeurIPS 2021 (Spotlight)
Vincent Sitzmann*, Semon Rezchikov*, William T. Freeman, Joshua B. Tenenbaum, Frédo Durand
Implicit Neural Representations with Periodic Activation Functions
NeurIPS 2020 (Oral)
Vincent Sitzmann*, Julien N. P. Martel*, Alexander W. Bergman, David B. Lindell, Gordon Wetzstein
MetaSDF: Meta-learning Signed Distance Functions
NeurIPS 2020
Vincent Sitzmann*, Eric R. Chan*, Richard Tucker, Noah Snavely, Gordon Wetzstein
State of the Art on Neural Rendering
Computer Graphics Forum 2020 - EG 2020 (STAR Report)
Ayush Tewari*, Ohad Fried*, Justus Thies*, Vincent Sitzmann*, Stephen Lombardi, Kalyan Sunkavalli, Ricardo Martin-Brualla, Tomas Simon, Jason Saragih, Matthias Nießner, Rohit Pandey, Sean Fanello, Gordon Wetzstein, Jun-Yan Zhu, Christian Theobalt, Maneesh Agrawala, Eli Shechtman, Dan B Goldman, Michael Zollhöfer
Inferring Semantic Information with 3D Neural Scene Representations
Amit Kohli*, Vincent Sitzmann*, Gordon Wetzstein
Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations
NeurIPS 2019 (Oral, Honorable Mention "Outstanding New Directions")
Vincent Sitzmann, Michael Zollhöfer, Gordon Wetzstein
DeepVoxels: Learning Persistent 3D Feature Embeddings
CVPR 2019 (Oral)
Vincent Sitzmann, Justus Thies, Felix Heide, Matthias Nießner, Gordon Wetzstein, Michael Zollhöfer
Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification
Scientific Reports
Julie Chang, Vincent Sitzmann, Xiong Dun, Wolfgang Heidrich, Gordon Wetzstein
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*, Xiong Dun, Stephen Boyd, Wolfgang Heidrich, Felix Heide, Gordon Wetzstein
Saliency in VR: How do people explore virtual environments?
IEEE VR 2018
Vincent Sitzmann*, Ana Serrano*, Amy Pavel, Maneesh Agrawala, Belen Masia, Diego Gutierrez, Gordon Wetzstein
Movie Editing and Cognitive Event Segmentation in Virtual Reality Video
Ana Serrano, Vincent Sitzmann, Jaime Ruiz-Borau, Gordon Wetzstein, Diego Gutierrez, Belen Masia
Towards a Machine-learning Approach for Sickness Prediction in 360° Stereoscopic Videos
IEEE VR 2018
Nitish Padmanaban*, Timon Ruban*, Vincent Sitzmann, Anthony M. Norcia, Gordon Wetzstein