32 citations · 39 across the 8 of their papers we have counts for
8 papers
LAC: Latent Action Composition for Skeleton-based Action Segmentation
Di Yang, Yaohui Wang, Antitza Dantcheva +4
Skeleton-based action segmentation requires recognizing composable actions in untrimmed videos. Current approaches decouple this problem by first extracting local visual features f…
Self-Supervised Video Representation Learning via Latent Time Navigation
Di Yang, Yaohui Wang, Quan Kong +4
Self-supervised video representation learning aimed at maximizing similarity between different temporal segments of one video, in order to enforce feature persistence over time. Th…
Human-Scene Network: A Novel Baseline with Self-rectifying Loss for Weakly supervised Video Anomaly Detection
Snehashis Majhi, Rui Dai, Quan Kong +3
Video anomaly detection in surveillance systems with only video-level labels (i.e. weakly-supervised) is challenging. This is due to, (i) the complex integration of human and scene…
Efficient and Accurate Skeleton-Based Two-Person Interaction Recognition Using Inter- and Intra-body Graphs
Yoshiki Ito, Quan Kong, Kenichi Morita +1
Skeleton-based two-person interaction recognition has been gaining increasing attention as advancements are made in pose estimation and graph convolutional networks. Although the a…
Mask Atari for Deep Reinforcement Learning as POMDP Benchmarks
Yang Shao, Quan Kong, Tadayuki Matsumura +3
We present Mask Atari, a new benchmark to help solve partially observable Markov decision process (POMDP) problems with Deep Reinforcement Learning (DRL)-based approaches. To achie…
Robust Unsupervised Multi-Object Tracking in Noisy Environments
C. -H. Huck Yang, Mohit Chhabra, Y. -C. Liu +3
Physical processes, camera movement, and unpredictable environmental conditions like the presence of dust can induce noise and artifacts in video feeds. We observe that popular uns…
Cycle-Contrast for Self-Supervised Video Representation Learning
Quan Kong, Wenpeng Wei, Ziwei Deng +2
We present Cycle-Contrastive Learning (CCL), a novel self-supervised method for learning video representation. Following a nature that there is a belong and inclusion relation of v…
Active Generative Adversarial Network for Image Classification
Quan Kong, Bin Tong, Martin Klinkigt +3
Sufficient supervised information is crucial for any machine learning models to boost performance. However, labeling data is expensive and sometimes difficult to obtain. Active lea…