45 citations · 256 across the 14 of their papers we have counts for
17 papers
End-to-End Self-Supervised RGB-T Tracking without Modality Misleading
Shenglan Li, Rui Yao, Kunyang Sun +4
RGB-T object tracking leverages the complementary characteristics of visible and thermal infrared modalities to improve robustness under adverse conditions. Existing supervised met…
Vision-Language Guided Hyperspectral Object Tracking via Semantics Fusion and Contextual Template Updating
Rui Yao, Yuhong Zhang, Kunyang Sun +4
Hyperspectral object tracking (HOT) leverages the rich spectral information provided by hyperspectral videos (HSVs), offering substantial potential for object tracking. However, ef…
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…
Semi-supervised Image Dehazing via Expectation-Maximization and Bidirectional Brownian Bridge Diffusion Models
Bing Liu, Le Wang, Mingming Liu +5
Existing dehazing methods deal with real-world haze images with difficulty, especially scenes with thick haze. One of the main reasons is the lack of real-world paired data and rob…
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…
OrientedFormer: An End-to-End Transformer-Based Oriented Object Detector in Remote Sensing Images
Jiaqi Zhao, Zeyu Ding, Yong Zhou +4
Oriented object detection in remote sensing images is a challenging task due to objects being distributed in multi-orientation. Recently, end-to-end transformer-based methods have…
Leveraging Large-Scale Pretrained Vision Foundation Models for Label-Efficient 3D Point Cloud Segmentation
Shichao Dong, Fayao Liu, Guosheng Lin
Recently, large-scale pre-trained models such as Segment-Anything Model (SAM) and Contrastive Language-Image Pre-training (CLIP) have demonstrated remarkable success and revolution…
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…
TextDCT: Arbitrary-Shaped Text Detection via Discrete Cosine Transform Mask
Yuchen Su, Zhiwen Shao, Yong Zhou +4
Arbitrary-shaped scene text detection is a challenging task due to the variety of text changes in font, size, color, and orientation. Most existing regression based methods resort…
Vehicle Re-Identification Based on Complementary Features
Cunyuan Gao, Yi Hu, Yi Zhang +3
In this work, we present our solution to the vehicle re-identification (vehicle Re-ID) track in AI City Challenge 2020 (AIC2020). The purpose of vehicle Re-ID is to retrieve the sa…
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…
Video Object Segmentation and Tracking: A Survey
Rui Yao, Guosheng Lin, Shixiong Xia +2
Object segmentation and object tracking are fundamental research area in the computer vision community. These two topics are diffcult to handle some common challenges, such as occl…
CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning
Chi Zhang, Guosheng Lin, Fayao Liu +2
Recent progress in semantic segmentation is driven by deep Convolutional Neural Networks and large-scale labeled image datasets. However, data labeling for pixel-wise segmentation…
Efficient Eye Typing with 9-direction Gaze Estimation
Chi Zhang, Rui Yao, Jinpeng Cai
Vision based text entry systems aim to help disabled people achieve text communication using eye movement. Most previous methods have employed an existing eye tracker to predict ga…
Efficient Dense Labeling of Human Activity Sequences from Wearables using Fully Convolutional Networks
Rui Yao, Guosheng Lin, Qinfeng Shi +1
Recognizing human activities in a sequence is a challenging area of research in ubiquitous computing. Most approaches use a fixed size sliding window over consecutive samples to ex…