17 citations · 37 across the 22 of their papers we have counts for
7 papers · 1 filter
Referencing Where to Focus: Improving VisualGrounding with Referential Query
Yabing Wang, Zhuotao Tian, Qingpei Guo +4
Visual Grounding aims to localize the referring object in an image given a natural language expression. Recent advancements in DETR-based visual grounding methods have attracted co…
Towards Generalizable Multi-Object Tracking
Zheng Qin, Le Wang, Sanping Zhou +3
Multi-Object Tracking MOT encompasses various tracking scenarios, each characterized by unique traits. Effective trackers should demonstrate a high degree of generalizability acros…
Diversifying Query: Region-Guided Transformer for Temporal Sentence Grounding
Xiaolong Sun, Liushuai Shi, Le Wang +4
Temporal sentence grounding is a challenging task that aims to localize the moment spans relevant to a language description. Although recent DETR-based models have achieved notable…
Advancing Pre-trained Teacher: Towards Robust Feature Discrepancy for Anomaly Detection
Canhui Tang, Sanping Zhou, Yizhe Li +2
With the wide application of knowledge distillation between an ImageNet pre-trained teacher model and a learnable student model, unsupervised anomaly detection has witnessed a sign…
Learning Discriminative Spatio-temporal Representations for Semi-supervised Action Recognition
Yu Wang, Sanping Zhou, Kun Xia +1
Semi-supervised action recognition aims to improve spatio-temporal reasoning ability with a few labeled data in conjunction with a large amount of unlabeled data. Albeit recent adv…
Boosting Semi-Supervised Temporal Action Localization by Learning from Non-Target Classes
Kun Xia, Le Wang, Sanping Zhou +2
The crux of semi-supervised temporal action localization (SS-TAL) lies in excavating valuable information from abundant unlabeled videos. However, current approaches predominantly…
Recurrent Aligned Network for Generalized Pedestrian Trajectory Prediction
Yonghao Dong, Le Wang, Sanping Zhou +2
Pedestrian trajectory prediction is a crucial component in computer vision and robotics, but remains challenging due to the domain shift problem. Previous studies have tried to tac…