Publications

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

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2023

Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning
Boris Ivanovic, James Harrison, Marco Pavone
BITS: Bi-level Imitation for Traffic Simulation
Danfei Xu, Yuxiao Chen, Boris Ivanovic, Marco Pavone
ProgPrompt: Generating Situated Robot Task Plans Using Large Language Models
Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, Animesh Garg
Subpixel Deblurring of Anti-Aliased Raster Clip Art
Jinfan Yang, Nicholas Vining, Shakiba Kheradmand, Nathan Carr, Leonid Sigal, Alla Sheffer
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters
Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng
Robust and Controllable Object-Centric Learning through Energy-based Models
Ruixiang Zhang, Gerry Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull
Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis
Wan-Cyuan Fan, Yen-Chun Chen, Dongdong Chen, Yu Cheng, Lu Yuan, Frank Wang
BufFormer: A Generative ML Framework for Scalable Buffering
Rongjian Liang, Siddhartha Nath, Anand Rajaram, Jiang Hu, Haoxing (Mark) Ren

2022

"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
Niv Cohen, Rinon Gal, Eli Meirom, Gal Chechik, Yuval Atzmon
Elucidating the Design Space of Diffusion-Based Generative Models
Tero Karras, Miika Aittala, Timo Aila, Samuli Laine
NeurIPS Outstanding Paper
LION: Latent Point Diffusion Models for 3D Shape Generation
Xiaohui Zeng, Arash Vahdat, Francis Williams, Zan Gojcic, Or Litany, Sanja Fidler, Karsten Kreis
GENIE: Higher-Order Denoising Diffusion Solvers
Tim Dockhorn, Arash Vahdat, Karsten Kreis
Diffusion Models for Adversarial Purification
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs
Jiteng Mu, Shalini De Mello, Zhiding Yu, Nuno Vasconcelos, Xiaolong Wang, Sifei Liu
Polymorphic-GAN: Generating Aligned Samples across Multiple Domains with Learned Morph Maps
Seung Wook Kim, Karsten Kreis, Daiqing Li, Antonio Torralba, Sanja Fidler
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
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
Rinon Gal, Or Patashnik, Haggai Maron, Amir Bermano, Gal Chechik, Daniel Cohen-Or
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
DeePattern: Layout Pattern Generation with Transforming Convolutional Auto-Encoder
Haoyu Yang, Shuhe Li, Wen Chen, Piyush Pathak, Frank Gennari, Ya-Chieh Lai, Bei Yu
Best Paper Award

2021

ATISS: Autoregressive Transformers for Indoor Scene Synthesis
Despoina Paschalidou, Amlan Kar, Maria Shugrina, Karsten Kreis, Andreas Geiger, Sanja Fidler
Alias-Free Generative Adversarial Networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, Timo Aila
EditGAN: High-Precision Semantic Image Editing
Huan Ling, Karsten Kreis, Daiqing Li, Seung Wook Kim, Antonio Torralba, Sanja Fidler
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
Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization
Daiqing Li, Junlin Yang, Karsten Kreis, Antonio Torralba, Sanja Fidler
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models
Zhisheng Xiao, Karsten Kreis, Jan Kautz, Arash Vahdat

2020

Training Generative Adversarial Networks with Limited Data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, Timo Aila
Variational Amodal Object Completion
Huan Ling, David Acuna, Karsten Kreis, Seung Wook Kim, Sanja Fidler
Neural FFTs for Universal Texture Image Synthesis
Morteza Mardani, Guilin Liu, Aysegul Dundar, Shiqiu Liu, Andrew Tao, Bryan Catanzaro
Semi-Supervised StyleGAN for Disentanglement Learning
Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Anima Anandkumar