30 citations · 59 across the 7 of their papers we have counts for
7 papers
Responsible Task Automation: Empowering Large Language Models as Responsible Task Automators
Zhizheng Zhang, Xiaoyi Zhang, Wenxuan Xie +1
The recent success of Large Language Models (LLMs) signifies an impressive stride towards artificial general intelligence. They have shown a promising prospect in automatically com…
Unifying Layout Generation with a Decoupled Diffusion Model
Mude Hui, Zhizheng Zhang, Xiaoyi Zhang +3
Layout generation aims to synthesize realistic graphic scenes consisting of elements with different attributes including category, size, position, and between-element relation. It…
A Semi-supervised Sensing Rate Learning based CMAB Scheme to Combat COVID-19 by Trustful Data Collection in the Crowd
Jianheng Tang, Kejia Fan, Wenxuan Xie +6
The recruitment of trustworthy and high-quality workers is an important research issue for MCS. Previous studies either assume that the qualities of workers are known in advance, o…
Sparse MLP for Image Recognition: Is Self-Attention Really Necessary?
Chuanxin Tang, Yucheng Zhao, Guangting Wang +3
Transformers have sprung up in the field of computer vision. In this work, we explore whether the core self-attention module in Transformer is the key to achieving excellent perfor…
Unsupervised Visual Representation Learning by Tracking Patches in Video
Guangting Wang, Yizhou Zhou, Chong Luo +3
Inspired by the fact that human eyes continue to develop tracking ability in early and middle childhood, we propose to use tracking as a proxy task for a computer vision system to…
Detect or Track: Towards Cost-Effective Video Object Detection/Tracking
Hao Luo, Wenxuan Xie, Xinggang Wang +1
State-of-the-art object detectors and trackers are developing fast. Trackers are in general more efficient than detectors but bear the risk of drifting. A question is hence raised…
Learning to Update for Object Tracking with Recurrent Meta-learner
Bi Li, Wenxuan Xie, Wenjun Zeng +1
Model update lies at the heart of object tracking. Generally, model update is formulated as an online learning problem where a target model is learned over the online training set.…