7 papers
Value-Guided Repulsion for Offline Reinforcement Learning
Yixue Hao, Jiahao Zhang, Jiesong Lian +5
Drifting models have emerged as a highly efficient and stable paradigm for policy design in offline reinforcement learning (RL). However, standard drift policies determine repulsio…
CoDy: Codec Dynamics as Complementary Priors for Unsupervised Temporal Action Localization
Tianyu Yan, Qingyi Yang, Qin Yang +5
Unsupervised temporal action localization (UTAL) aims to identify action categories and localize their temporal boundaries without annotation supervision. Existing methods typicall…
DepthTile: Depth-Guided Existing-Image Self-Tiling with Input-Side Tileability Assessment
Rui Wang, Xi Chen, Hui Dai +4
Existing-image self-tiling aims to transform a given image into a seamlessly repeatable tile while preserving its original semantics and local details. This task requires weak edit…
Counting Beyond Instances: A Benchmark for Group-Individual Object Counting
Rui Wang, Junyi Huang, Jiahui Li +4
Visual counting is commonly formulated at the instance level, aiming to estimate how many objects of a queried category appear in an image. However, real-world counting often invol…
Resource Efficient Sleep Staging via Multi-Level Masking and Prompt Learning
Lejun Ai, Yulong Li, Haodong Yi +5
Automatic sleep staging plays a vital role in assessing sleep quality and diagnosing sleep disorders. Most existing methods rely heavily on long and continuous EEG recordings, whic…
DCMAC: Demand-aware Customized Multi-Agent Communication via Upper Bound Training
Dongkun Huo, Huateng Zhang, Yixue Hao +4
Efficient communication can enhance the overall performance of collaborative multi-agent reinforcement learning. A common approach is to share observations through full communicati…
Multimodal Physiological Signals Representation Learning via Multiscale Contrasting for Depression Recognition
Kai Shao, Rui Wang, Yixue Hao +3
Depression recognition based on physiological signals such as functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) has made considerable progress. However,…