Generative AI

Associated Publications

2023

VerilogEval: Evaluating Large Language Models for Verilog Code Generation

Mingjie Liu, Nathaniel Pinckney, Brucek Khailany, Mark Ren

2023 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)

Flexible Isosurface Extraction for Gradient-Based Mesh Optimization

Tianchang Shen, Jacob Munkberg, Jon Hasselgren, Kangxue Yin, Zian Wang, Wenzheng Chen, Zan Gojcic, Sanja Fidler, Nicholas Sharp, Jun Gao

ACM Transactions On Graphics (SIGGRAPH 2023)

Live 3D Portrait: Real-Time Radiance Fields for Single-Image Portrait View Synthesis

Alexander Trevithick, Matthew Chan, Michael Stengel, Eric R. Chan, Chao Liu, Zhiding Yu, Sameh Khamis, Manmohan Chandraker, Ravi Ramamoorthi, Koki Nagano

ACM Transactions On Graphics (SIGGRAPH 2023)

AI-Mediated 3D Video Conferencing

Michael Stengel, Koki Nagano, Chao Liu, Matthew Chan, Alex Trevithick, Shalini De Mello, Jonghyun Kim, David Luebke, Amrita Mazumdar, Shengze Wang, Mayoore Jaiswal

ACM SIGGRAPH Emerging Technologies

A Hybrid Generator Architecture for Controllable Face Synthesis

Dann Mensah, Nam Hee Kim, Miika Aittala, Samuli Laine, Jaakko Lehtinen

SIGGRAPH 2023

IGB: Addressing The Gaps In Labeling, Features, Heterogeneity, and Size of Public Graph Datasets for Deep Learning Research

Arpandeep Khatua, Vikram Sharma Mailthody, Bhagyashree Taleka, Tengfei Ma, Xiang Song, Wen-mei Hwu

KDD'23

Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields

Guojin Chen, Zehua Pei, Haoyu Yang, Yuzhe Ma, Bei Yu, Martin Wong

60th ACM/IEEE Design Automation Conference

StructDiffusion: Language-Guided Creation of Physically-Valid Structures using Unseen Objects

Weiyu Liu, Yilun Du, Tucker Hermans, Sonia Chernova, Chris Paxton

Robotics: Science and Systems (RSS) 2023

FreeNeRF: Improving Few-shot Neural Rendering with Free Frequency Regularization

Jiawei Yang, Marco Pavone, Yue Wang

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models

Jiarui Xu, Sifei Liu, Arash Vahdat, Wonmin Byeon, Xiaolong Wang, Shalini De Mello

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2023

Hightlight top 10%

Planning for Multi-Object Manipulation with Graph Neural Network Relational Classifiers

Yixuan Huang, Adam Conkey, Tucker Hermans

IEEE International Conference on Robotics and Automation (ICRA)

Guided Conditional Diffusion for Controllable Traffic Simulation

Ziyuan Zhong, Davis Rempe, Danfei Xu, Yuxiao Chen, Sushant Veer, Gerry Che, Baishakhi Ray, Marco Pavone

IEEE International Conference on Robotics and Automation (ICRA) 2023

Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-Learning

Boris Ivanovic, James Harrison, Marco Pavone

IEEE International Conference on Robotics and Automation (ICRA) 2023

BITS: Bi-level Imitation for Traffic Simulation

Danfei Xu, Yuxiao Chen, Boris Ivanovic, Marco Pavone

IEEE International Conference on Robotics and Automation (ICRA) 2023

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

The International Conference on Robotics and Automation (ICRA)

Subpixel Deblurring of Anti-Aliased Raster Clip Art

Jinfan Yang, Nicholas Vining, Shakiba Kheradmand, Nathan Carr, Leonid Sigal, Alla Sheffer

Computer Graphics Forum (Proc. Eurographics 2023)

CALM: Conditional Adversarial Latent Models for Directable Virtual Characters

Chen Tessler, Yoni Kasten, Yunrong Guo, Shie Mannor, Gal Chechik, Xue Bin Peng

SIGGRAPH 2023

Robust and Controllable Object-Centric Learning through Energy-based Models

Ruixiang Zhang, Gerry Che, Boris Ivanovic, Renhao Wang, Marco Pavone, Yoshua Bengio, Liam Paull

International Conference on Learning Representations (ICLR) 2023

Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis

Wan-Cyuan Fan, Yen-Chun Chen, Dongdong Chen, Yu Cheng, Lu Yuan, Frank Wang

AAAI 2023

BufFormer: A Generative ML Framework for Scalable Buffering

Rongjian Liang, Siddhartha Nath, Anand Rajaram, Jiang Hu, Mark Ren

28th Asia and South Pacific Design Automation Conference

2022

Elucidating the Design Space of Diffusion-Based Generative Models

Tero Karras, Miika Aittala, Timo Aila, Samuli Laine

NeurIPS 2022 (oral)

NeurIPS Outstanding Paper

CoordGAN: Self-Supervised Dense Correspondences Emerge from GANs

Jiteng Mu, Shalini De Mello, Zhiding Yu, Nuno Vasconcelos, Xiaolong Wang, Sifei Liu

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022

Diffusion Models for Adversarial Purification

Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar

International Conference on Machine Learning (ICML), 2022

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

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2022

Oral presentation

StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators

Rinon Gal, Or Patashnik, Haggai Maron, Amir Bermano, Gal Chechik, Daniel Cohen-Or

SIGGRAPH 2022

Score-Based Generative Modeling with Critically-Damped Langevin Diffusion

Tim Dockhorn, Arash Vahdat, Karsten Kreis

International Conference on Learning Representations (ICLR), 2022 (Spotlight)

Tackling the Generative Learning Trilemma with Denoising Diffusion GANs

Zhisheng Xiao, Karsten Kreis, Arash Vahdat

International Conference on Learning Representations (ICLR) 2022 (Spotlight)

DeePattern: Layout Pattern Generation with Transforming Convolutional Auto-Encoder