NVIDIA at CVPR 2023

June 18–22, 2023

Connect with NVIDIA researchers at this year’s Computer Vision and Pattern Recognition (CVPR) online conference and learn more about the work we’ll be presenting—including forty eight papers. Come see how NVIDIA Research collaborates with CVPR members to deliver AI breakthroughs across the community.

It all happens June 18–22, 2023.

NVIDIA Research Papers at CVPR 2023

NVIDIA’s accepted papers at this year’s online CVPR feature a range of groundbreaking research in the field of computer vision. From human motion forecasting to extracting triangular 3D models, materials, and lighting from images, explore the work NVIDIA is bringing to the CVPR community.

* Denotes equal contribution to the paper.

Magic3D: High-Resolution Text-to-3D Content Creation

Chen-Hsuan Lin*, Jun Gao*, Luming Tang*, Towaki Takikawa*, Xiaohui Zeng*, Xun Huang, Karsten Kreis, Sanja Fidler*, Ming-Yu Liu*, Tsung-Yi Lin | Coming Soon

Align Your Latents: High-Resolution Video Synthesis With Latent Diffusion Models

Andreas Blattmann*, Robin Rombach*, Huan Ling*, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, Karsten Kreis | Coming Soon

Neural Kernel Surface Reconstruction

Jiahui Huang, Zan Gojcic, Matan Atzmon, Or Litany, Sanja Fidler, Francis Williams | Coming Soon

Affordance Diffusion: Synthesizing Hand-Object Interactions

Yufei Ye, Xueting Li, Abhinav Gupta, Shalini De Mello, Stan Birchfield, Jiaming Song, Shubham Tulsiani, Sifei Liu | Coming Soon

Neuralangelo: High-Fidelity Neural Surface Reconstruction

Zhaoshuo Li, Thomas Muller, Alex Evans, Russell H. Taylor, Mathias Unberath, Ming-Yu Liu, Chen-Hsuan Lin | Coming Soon

Zero-Shot Pose Transfer for Unrigged Stylized 3D Characters

Jiashun Wang, Xueting Li, Sifei Liu, Shalini De Mello, Orazio Gallo, Xiaolong Wang, Jan Kautz | Coming Soon

The Best Defense Is a Good Offense: Adversarial Augmentation Against Adversarial Attacks

Luri Frosio, Jan Kautz | Coming Soon

DiffCollage: Parallel Generation of Large Content With Diffusion Models

Qinsheng Zhang, Jiaming Song, Xun Huang, Yongxin Chen, Ming-Yu Liu | Coming Soon

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

Jiawei Yang, Marco Pavone, and Yue Wang | Coming Soon

Vision Transformers are Good Mask Auto-Labelers

Shiyi Lan, Xitong Yang, Zhiding Yu, Zuxuan Wu, Jose M. Alvarez, Anima Anandkumar | Coming Soon

VoxFormer: Sparse Voxel Transformer for Camera-based 3D Semantic Scene Completion

SYiming Li, Zhiding Yu, Chris Choy, Chaowei Xiao, Jose M. Alvarez, Sanja Fidler, Chen Feng, Anima Anandkumar | Coming Soon

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

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

GazeNeRF: 3D-Aware Gaze Redirection With Neural Radiance Fields

Alessandro Ruzzi, Xiangwei Shi, Xi Wang, Gengyan Li, Shalini De Mello, Hyung Jin Chang, Xucong Zhang, Otmar Hilliges | Coming Soon

Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion

Davis Rempe, Zhengyi Luo, Xue Bin Peng, Ye Yuan, Kris M. Kitani, Karsten Kreis, Sanja Fidler, Or Litany | Coming Soon

Heterogeneous Continual Learning

Divyam Madaan, Hongxu Yin, Wonmin Byeon, Jan Kautz, Pavlo Molchanov | Coming Soon

Global Vision Transformer Pruning With Hessian-Aware Saliency

Huanrui Yang, Hongxu Yin, Maying Shen, Pavlo Molchanov, Hai Li, Jan Kautz | Coming Soon

Recurrence Without Recurrence: Stable Video Landmark Detection With Deep Equilibrium Models

Paul Micaelli, Pavlo Molchanov, Arash Vahdat, Hongxu Yin, Jan Kautz | Coming Soon

Fast Monocular Scene Reconstruction With Global-Sparse Local-Dense Grids

Wei Dong, Chris Choy, Charles Loop, Or Litany, Yuke Zhu | Coming Soon

TTA-COPE: Test-Time Adaptation for Category-Level Object Pose Estimation

Taeyeop Lee, Jonathan Tremblay, Valts Blukis, Bowen Wen, Byeong-Uk Lee, Inkyu Shin, Stan Birchfield, In So Kweon, Kuk-Jin Yoon | Coming Soon

NeuralField-LDM: Scene Generation With Hierarchical Latent Diffusion Models

Seung Wook Kim*, Bradley Brown*, Kangxue Yin, Karsten Kreis, Katja Schwarz, Daiqing Li, Robin Rombach, Antonio Torralba, Sanja Fidler | Coming Soon

Neural Fields Meet Explicit Geometric Representations for Inverse Rendering of Urban Scenes

Zian Wang, Tianchang Shen, Jun Gao, Shengyu Huang, Jacob Munkberg, Jon Hasselgren, Zan Gojcic, Wenzheng Chen, Sanja Fidler | Coming Soon

Learning 3D Reconstruction Network From 2D StyleGAN

Aysegul Dundar, Jun Gao, Andrew Tao, Bryan Catanzaro | Coming Soon

Learning Human-to-Robot Handovers From Point Clouds

Sammy Christen, Wei Yang, Claudia Pérez-D'Arpino, Otmar Hilliges, Dieter Fox, Yu-Wei Chao | Coming Soon

Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects

Bowen Wen, Jonathan Tremblay, Valts Blukis, Stephen Tyree, Thomas Müller, Alex Evans, Dieter Fox, Jan Kautz, Stan Birchfield | Coming Soon

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Deep Dive

Accelerating Digital Pathology Workflows Using cuCIM and NVIDIA GPUDirect Storage

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Image courtesy of Microsoft Bing

Increasing Throughput and Reducing Cost for AI-Based Computer Vision With CV-CUDA

CV-CUDA® open beta optimizes pre- and postprocessing for an end-to-end throughput improvement of up to 49X over OpenCV CPU. CV-CUDA enables real-time, high-performance, cloud-scale applications that demand lower latency and higher throughput.

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NVIDIA Omniverse

Check out the GTC Spring 2023 montage of NVIDIA Omniverse™ foundational technology in action.

NVIDIA Research AI Playground

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