Researchers, developers, and engineers worldwide are gathering virtually this year for the annual Conference on Computer Vision and Pattern Recognition (CVPR) from June 19th to June 25th. Throughout the week, NVIDIA Research will present their recent computer vision-related projects via presentations and interactive Q&As.
The nearly 30 accepted papers from NVIDIA range from simulating dynamic driving environments, to powering neural architecture search for medical imaging.
Here are a few featured papers:
DriveGAN: Towards a Controllable High-Quality Neural Simulation
Authors: Seung Wook Kim (University of Toronto, NVIDIA)*; Jonah Philion (University of Toronto, NVIDIA); Antonio Torralba (MIT); Sanja Fidler (University of Toronto, NVIDIA)
DriveGAN is a fully differentiable simulator, it further allows for re-simulation of a given video sequence, offering an agent to drive through a recorded scene again, possibly taking different actions.
The talk will be live on Tuesday, June 22, 2021 at 10:00pm EST
DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation
Authors: Yufan He (Johns Hopkins University)*; Dong Yang (NVIDIA); Holger R Roth (NVIDIA); Can Zhao (NVIDIA); Daguang Xu (NVIDIA)
From the abstract: In this work, we focus on three important aspects of NAS in 3D medical image segmentation: flexible multi-path network topology, high search efficiency, and budgeted GPU memory usage. Our method achieves the state-of-the-art performance and the top ranking on the MSD challenge leaderboard.
The talk will be live on Tuesday, June 22, 2021 at 10:00 pm EST
To view the complete list of NVIDIA Research accepted papers, workshop and tutorials, demos, and to explore job opportunities at NVIDIA, visit the NVIDIA at CVPR 2021 website.
