Bio

I am a fourth-year Ph.D. student in the Stanford Computational Imaging Laboratory, advised by Prof. Gordon Wetzstein. My research interest lies in neural scene representations - the way neural networks learn to represent information on our 3D 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. I have previously worked on differentiable camera pipelines, VR and human perception.

News

March 2020
Our state-of-the-art report on neural rendering was accepted to Eurographics 2020. Drop by our tutorial!
November 2019
Our paper "Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representations" wins an honorable mention for "Outstanding New Directions" at NeurIPS 2019! Watch my talk here.
May 2019
I will join Prof. Noah Snavely's group at the Google NYC office over the summer and continue working on deep learning for scene understanding and novel view synthesis.
March 2019
Our paper "DeepVoxels: Learning Persistent 3D Feature Embeddings" was accepted to CVPR as an oral! I will be in Los Angeles from June 16 to June 21 to present the paper.

Publications

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 with3D Neural Scene Representations
arXiv preprint
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
SIGGRAPH 2018
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
SIGGRAPH 2017
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