Publications

Our publications provide insight into some of our leading-edge research.

Filters

Filters

Publication Year

Research Areas

Events

2022

GENIE: Higher-Order Denoising Diffusion Solvers
Tim Dockhorn, Arash Vahdat, Karsten Kreis
Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty
Boris Ivanovic, Kuan-Hui Lee, Pavel Tokmakov, Blake Wulfe, Adrien Gaidon, Marco Pavone
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction
Yulong Cao, Chaowei Xiao, Anima Anandkumar, Danfei Xu, Marco Pavone
LANA: Latency Aware Network Acceleration
Pavlo Molchanov, Jimmy Hall, Hongxu Danny Yin, Jan Kautz, Nicolo Fusi, Arash Vahdat
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H. Bermano, Gal Chechik, Daniel Cohen-Or
Top 25%
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
Thomas Müller, Alex Evans, Christoph Schied, Alex Keller
Best Technical Paper, SIGGRAPH 2022
THE BEST INVENTIONS OF 2022, TIME
Whose Track Is It Anyway? Improving Robustness to Tracking Errors with Affinity-Based Prediction
Xinshuo Weng, Boris Ivanovic, Kris Kitani, Marco Pavone
ScePT: Scene-consistent, Policy-based Trajectory Predictions for Planning
Yuxiao Chen, Boris Ivanovic, Marco Pavone
Polymorphic-GAN: Generating Aligned Samples across Multiple Domains with Learned Morph Maps
Seung Wook Kim, Karsten Kreis, Daiqing Li, Antonio Torralba, Sanja Fidler
GroupViT: Semantic Segmentation Emerges from Text Supervision
Jiarui Xu, Shalini De Mello, Sifei Liu, Wonmin Byeon, Thomas Breuel, Jan Kautz, Xiaolong Wang
FreeSOLO: Learning to Segment Objects without Annotations
Xinlong Wang, Zhiding Yu, Shalini De Mello, Jan Kautz, Anima Anandkumar, Chunhua Shen, Jose M. Alvarez
Efficient Geometry-aware 3D Generative Adversarial Networks
Eric R. Chan, Connor Z. Lin, Matthew A. Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas Guibas, Jonathan Tremblay, Sameh Khamis, Tero Karras, Gordon Wetzstein
Oral
BigDatasetGAN: Synthesizing ImageNet with Pixel-wise Annotations
Daiqing Li, Huan Ling, Seung Wook Kim, Karsten Kreis, Adela Barriuso, Sanja Fidler, Antonio Torralba
Injecting Planning-Awareness into Prediction and Detection Evaluation
Boris Ivanovic, Marco Pavone
MTP: Multi-Hypothesis Tracking and Prediction for Reduced Error Propagation
Xinshuo Weng, Boris Ivanovic, Marco Pavone
Propagating State Uncertainty Through Trajectory Forecasting
Boris Ivanovic, Yifeng Lin, Shubham Shrivastava, Punarjay Chakravarty, Marco Pavone
A Dataset and Explorer for 3D Signed Distance Functions
Towaki Takikawa, Andrew Glassner, Morgan McGuire
Neural Fields in Visual Computing and Beyond
Yiheng Xie, Towaki Takikawa, Shunsuke Saito, Or Litany, Shiqin Yan, Numair Khan, Federico Tombari, James Tompkin, Vincent Sitzmann, Srinath Sridhar
Efficient Token Mixing for Transformers via Adaptive Fourier Neural Operators
"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
Niv Cohen, Rinon Gal, Gal Chechik, Yuval Atzmon
Oral
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion
Tim Dockhorn, Arash Vahdat, Karsten Kreis
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs
Zhisheng Xiao, Karsten Kreis, Arash Vahdat

2021

EditGAN: High-Precision Semantic Image Editing
Huan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba, Sanja Fidler
KAMA: 3D Keypoint Aware Body Mesh Articulation
Umar Iqbal, Kevin Xie, Kelly Guo, Jan Kautz, Pavlo Molchanov
Standard vs. Learning-based Codecs for Real Time Endoscopic Video Transmission
Iuri Frosio, Aldo Marzullo, Martina Golini, Elena De Momi, Michele Catellani, Francesco Calimeri, Giuseppe Fiameni
Extracting Triangular 3D Models, Materials, and Lighting From Images
Jacob Munkberg, Jon Hasselgren, Tianchang Shen, Jun Gao, Wenzheng Chen, Alex Evans, Thomas Müller, Sanja Fidler
Noise-Aware Video Saliency Prediction
Ekta Prashnani, Orazio Gallo, Joohwan Kim, Josef Spjut, Pradeep Sen, Iuri Frosio
A Contrastive Learning Approach for Training Variational Autoencoder Priors
Jyoti Aneja, Alexander Schwing, Jan Kautz, Arash Vahdat
Controllable and Compositional Generation with Latent-Space Energy-Based Models
Weili Nie, Arash Vahdat, Anima Anandkumar
Don’t Generate Me: Training Differentially Private Generative Models with Sinkhorn Divergence
Tianshi Cao, Alex Bie, Arash Vahdat, Sanja Fidler, Karsten Kreis
Score-based Generative Modeling in Latent Space
Arash Vahdat, Karsten Kreis, Jan Kautz
Weakly-Supervised Physically Unconstrained Gaze Estimation
Rakshit Kothari, Shalini De Mello, Umar Iqbal, Wonmin Byeon, Seonwook Park, Jan Kautz
Oral