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NVIDIA at CVPR 2020

Engage with NVIDIA researchers to learn more about the work we’ll be presenting at this year’s Computer Vision and Pattern Recognition (CVPR) online conference. NVIDIA researchers will present fifteen papers and posters on June 14–19, 2020.

NVIDIA research features AI breakthroughs with collaborations across the CVPR community.

Presentations

NVIDIA’s accepted papers at this year’s online CVPR feature a range of groundbreaking research in the field of computer vision. From simulating dynamic gaming environments to powering coarse-to-fine neural architecture search for medical imaging, explore the work NVIDIA is bringing to the CVPR community.

Learning to Simulate Dynamic Environments With GameGAN

Bi3D: Stereo Depth Estimation via Binary Classifications

Meshlet Priors for 3D Mesh Reconstruction

Self-Supervised Viewpoint Learning From Image Collections

Two-Shot Spatially Varying BRDF and Shape Estimation

C2FNAS: Coarse-to-Fine Neural Architecture Search for 3D Medical Image Segmentation

Weakly Supervised 3D Human Pose Learning via Multi-View Images in the Wild

Umar Iqbal | Pavlo Molchanov | Jan Kautz | Paper | CVPR Talk

Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths fFrom a Monocular Camera

Analyzing and Improving the Image Quality of StyleGAN

Panoptic-Based Image Synthesis

Dreaming to Distill: Data-Free Knowledge Transfer via DeepInversion

LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation

Instance-Aware, Context-Focused, and Memory-Efficient Weakly Supervised Object Detection

UNAS: Differentiable Architecture Search Meets Reinforcement Learning

Learning to Evaluate Perception Models Using Planner-Centric Metrics

Jonah Philion | Amlan Kar | Sanja Fidler | Paper | CVPR Talk

Workshops and Tutorials

Join NVIDIA at CVPR workshops and tutorials to engage with a diverse team of experts, expand your knowledge, and grow your skills with hands-on training.

3rd Workshop and Challenge on Learned Image Compression

4th AI City Challenge

7th DeepVision Workshop

2nd Workshop on Learning from Unlabeled Videos (LUV)

AI for Content Creation

DynaVis: The 2nd International Workshop on Dynamic Scene Reconstruction

Image Matching: Local Features and Beyond

New Trends in Image Restoration and Enhancement Workshop and Challenges (NTIRE)

Learning 3D Generative Models

The 3rd Workshop and Prize Challenge: Bridging the Gap between Computational Photography and Visual Recognition (UG2+) in conjunction with IEEE CVPR 2020

1st VizWiz Grand Challenge: Describing Images from Blind People

Women in Computer Vision (WiCV)

Workshop on Efficient Deep Learning for Computer Vision

The First Workshop and Challenge on Sim2Real Visual Navigation in Indoor Environments

CLVISION 1st Workshop on Continual Learning in Computer Vision

DIRA Workshop and Challenge Diagram Image Retrieval and Analysis (DIRA): Representation, Learning, and Similarity Metrics

Novel View Synthesis: From Depth-Based Warping to Multi-Plane Images and Beyond (Tutorial)

Deep Dive

Jarvis Live Webinar | July 7

Learn how to build speech recognition, natural language understanding, and speech synthesis services with NVIDIA NeMo and Jarvis. First, we'll cover the basics of the NeMo toolkit for training and fine-tuning conversational AI models on your data. Then, we'll discuss how to use Jarvis to deploy and combine these services into a complete conversational AI solution.

Inside NVIDIA's Multi-Instance GPU Feature

NVIDIA's latest GPUs have an important new feature: Multi-Instance GPU (MIG). MIG allows large GPUs to be effectively divided into multiple instances of smaller GPUs. The primary benefit of the MIG feature is increasing GPU utilization by enabling the GPU to be efficiently shared by unrelated parallel compute workloads on bare metal, GPU pass-through, or on multiple vGPUs.

Watch Recording

Featured Projects

Watch an Autonomous Vehicle Navigate Around Silicon Valley

NVIDIA DRIVE Constellation^™ enables high-fidelity, end-to-end simulation for development and validation of autonomous vehicles.

Watch Video

Misty: The Making of NVIDIA’s 3D AI Chatbot

Misty is NVIDIA’s take on a 3D animated, intelligent, interactive chatbot, brought to life in Omniverse. Misty connects our state of the art Jarvis conversational AI technology to our state of the art AI computer graphics technology.

Watch Video

Ride the Fast Lane to AI Productivity with Multi-Instance GPU

Dramatic Gains in Performance and Utilization with Multi-Instance GPUs

Multi-Instance GPU (MIG) mode on the NVIDIA A100 Tensor Core GPU can guarantee performance for up to seven jobs running concurrently on the same GPU.

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Synthesizing High-Resolution Images with GANs

Developed by NVIDIA researchers, StyleGAN2 yields state-of-the-art results in data-driven unconditional generative image modeling.

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Protect Healthcare Data with Federated Learning

NVIDIA Clara^™ Federated Learning is a reference application for distributed, collaborative AI model training that preserves patient privacy.

Watch Video

The Robotics Factory of the Future

NVIDIA Isaac Sim^™is the industry’s first robotic AI development platform with simulation, navigation, and manipulation.

Watch Video

A Big Leap in AI Rendering

NVIDIA DLSS 2.0 is a DL-powered temporal video reconstruction algorithm that renders graphics at twice the speed of traditional techniques, with better image quality.

Watch Video

AI Inferencing at the Speed of Light

NVIDIA A100 GPUs deliver significantly faster performance for image classification workloads.

Watch Video

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NVIDIA at CVPR 2020

Presentations

Workshops and Tutorials

Deep Dive

Jarvis Live Webinar | July 7

Inside NVIDIA's Multi-Instance GPU Feature

Featured Projects

Watch an Autonomous Vehicle Navigate Around Silicon Valley

Misty: The Making of NVIDIA’s 3D AI Chatbot

Dramatic Gains in Performance and Utilization with Multi-Instance GPUs

Synthesizing High-Resolution Images with GANs

Protect Healthcare Data with Federated Learning

The Robotics Factory of the Future

A Big Leap in AI Rendering

AI Inferencing at the Speed of Light

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LIKE NO PLACE
YOU’VE EVER WORKED