58 citations · 58 across the 1 of their papers we have counts for
6 papers
PointRend: Image Segmentation as Rendering
Alexander Kirillov, Yuxin Wu, Kaiming He +1
We present a new method for efficient high-quality image segmentation of objects and scenes. By analogizing classical computer graphics methods for efficient rendering with over- a…
Momentum Contrast for Unsupervised Visual Representation Learning
Kaiming He, Haoqi Fan, Yuxin Wu +2
We present Momentum Contrast (MoCo) for unsupervised visual representation learning. From a perspective on contrastive learning as dictionary look-up, we build a dynamic dictionary…
Feature Denoising for Improving Adversarial Robustness
Cihang Xie, Yuxin Wu, Laurens van der Maaten +2
Adversarial attacks to image classification systems present challenges to convolutional networks and opportunities for understanding them. This study suggests that adversarial pert…
Learning and Planning with a Semantic Model
Yi Wu, Yuxin Wu, Aviv Tamar +3
Building deep reinforcement learning agents that can generalize and adapt to unseen environments remains a fundamental challenge for AI. This paper describes progresses on this cha…
Group Normalization
Yuxin Wu, Kaiming He
Batch Normalization (BN) is a milestone technique in the development of deep learning, enabling various networks to train. However, normalizing along the batch dimension introduces…
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games
Yuandong Tian, Qucheng Gong, Wenling Shang +2
In this paper, we propose ELF, an Extensive, Lightweight and Flexible platform for fundamental reinforcement learning research. Using ELF, we implement a highly customizable real-t…