35 citations · 127 across the 7 of their papers we have counts for
7 papers
DTTNet: Improving Video Shadow Detection via Dark-Aware Guidance and Tokenized Temporal Modeling
Zhicheng Li, Kunyang Sun, Rui Yao +5
Video shadow detection confronts two entwined difficulties: distinguishing shadows from complex backgrounds and modeling dynamic shadow deformations under varying illumination. To…
Modality-Guided Dynamic Graph Fusion and Temporal Diffusion for Self-Supervised RGB-T Tracking
Shenglan Li, Rui Yao, Yong Zhou +5
To reduce the reliance on large-scale annotations, self-supervised RGB-T tracking approaches have garnered significant attention. However, the omission of the object region by erro…
Facial Action Unit Detection by Adaptively Constraining Self-Attention and Causally Deconfounding Sample
Zhiwen Shao, Hancheng Zhu, Yong Zhou +4
Facial action unit (AU) detection remains a challenging task, due to the subtlety, dynamics, and diversity of AUs. Recently, the prevailing techniques of self-attention and causal…
RQFormer: Rotated Query Transformer for End-to-End Oriented Object Detection
Jiaqi Zhao, Zeyu Ding, Yong Zhou +4
Oriented object detection presents a challenging task due to the presence of object instances with multiple orientations, varying scales, and dense distributions. Recently, end-to-…
CT-Net: Arbitrary-Shaped Text Detection via Contour Transformer
Zhiwen Shao, Yuchen Su, Yong Zhou +4
Contour based scene text detection methods have rapidly developed recently, but still suffer from inaccurate frontend contour initialization, multi-stage error accumulation, or def…
LRANet: Towards Accurate and Efficient Scene Text Detection with Low-Rank Approximation Network
Yuchen Su, Zhineng Chen, Zhiwen Shao +5
Recently, regression-based methods, which predict parameterized text shapes for text localization, have gained popularity in scene text detection. However, the existing parameteriz…
Facial Action Unit Detection via Adaptive Attention and Relation
Zhiwen Shao, Yong Zhou, Jianfei Cai +2
Facial action unit (AU) detection is challenging due to the difficulty in capturing correlated information from subtle and dynamic AUs. Existing methods often resort to the localiz…