153 citations · 297 across the 12 of their papers we have counts for
12 papers
Learning from Visual Observation via Offline Pretrained State-to-Go Transformer
Bohan Zhou, Ke Li, Jiechuan Jiang +1
Learning from visual observation (LfVO), aiming at recovering policies from only visual observation data, is promising yet a challenging problem. Existing LfVO approaches either on…
Pose Recognition with Cascade Transformers
Ke Li, Shijie Wang, Xiang Zhang +3
In this paper, we present a regression-based pose recognition method using cascade Transformers. One way to categorize the existing approaches in this domain is to separate them in…
Better Knowledge Retention through Metric Learning
Ke Li, Shichong Peng, Kailas Vodrahalli +1
In continual learning, new categories may be introduced over time, and an ideal learning system should perform well on both the original categories and the new categories. While de…
Multimodal Image Synthesis with Conditional Implicit Maximum Likelihood Estimation
Ke Li, Shichong Peng, Tianhao Zhang +1
Many tasks in computer vision and graphics fall within the framework of conditional image synthesis. In recent years, generative adversarial nets (GANs) have delivered impressive a…
Trajectory Normalized Gradients for Distributed Optimization
Jianqiao Wangni, Ke Li, Jianbo Shi +1
Recently, researchers proposed various low-precision gradient compression, for efficient communication in large-scale distributed optimization. Based on these work, we try to reduc…
On the Implicit Assumptions of GANs
Ke Li, Jitendra Malik
Generative adversarial nets (GANs) have generated a lot of excitement. Despite their popularity, they exhibit a number of well-documented issues in practice, which apparently contr…