300 citations · 1.2k across the 44 of their papers we have counts for
44 papers
AMatFormer: Efficient Feature Matching via Anchor Matching Transformer
Bo Jiang, Shuxian Luo, Xiao Wang +2
Learning based feature matching methods have been commonly studied in recent years. The core issue for learning feature matching is to how to learn (1) discriminative representatio…
Beyond Greedy Search: Tracking by Multi-Agent Reinforcement Learning-based Beam Search
Xiao Wang, Zhe Chen, Bo Jiang +3
To track the target in a video, current visual trackers usually adopt greedy search for target object localization in each frame, that is, the candidate region with the maximum res…
Tiny Object Tracking: A Large-scale Dataset and A Baseline
Yabin Zhu, Chenglong Li, Yao Liu +4
Tiny objects, frequently appearing in practical applications, have weak appearance and features, and receive increasing interests in meany vision tasks, such as object detection an…
MutualFormer: Multi-Modality Representation Learning via Cross-Diffusion Attention
Xixi Wang, Xiao Wang, Bo Jiang +2
Aggregating multi-modality data to obtain reliable data representation attracts more and more attention. Recent studies demonstrate that Transformer models usually work well for mu…
On the Robustness of "Robust reversible data hiding scheme based on two-layer embedding strategy"
Wen Yin, Longfei Ke, Zhaoxia Yin +2
In the paper "Robust reversible data hiding scheme based on two-layer embedding strategy" published in INS recently, Kumar et al. proposed a robust reversible data hiding (RRDH) sc…
Tracking by Joint Local and Global Search: A Target-aware Attention based Approach
Xiao Wang, Jin Tang, Bin Luo +3
Tracking-by-detection is a very popular framework for single object tracking which attempts to search the target object within a local search window for each frame. Although such l…
LasHeR: A Large-scale High-diversity Benchmark for RGBT Tracking
Chenglong Li, Wanlin Xue, Yaqing Jia +4
RGBT tracking receives a surge of interest in the computer vision community, but this research field lacks a large-scale and high-diversity benchmark dataset, which is essential fo…
Dynamic Attention guided Multi-Trajectory Analysis for Single Object Tracking
Xiao Wang, Zhe Chen, Jin Tang +4
Most of the existing single object trackers track the target in a unitary local search window, making them particularly vulnerable to challenging factors such as heavy occlusions a…
PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attack
Jie Wang, Zhaoxia Yin, Jin Tang +2
The studies on black-box adversarial attacks have become increasingly prevalent due to the intractable acquisition of the structural knowledge of deep neural networks (DNNs). Howev…
Viewpoint-aware Progressive Clustering for Unsupervised Vehicle Re-identification
Aihua Zheng, Xia Sun, Chenglong Li +1
Vehicle re-identification (Re-ID) is an active task due to its importance in large-scale intelligent monitoring in smart cities. Despite the rapid progress in recent years, most ex…
RGBT Tracking via Multi-Adapter Network with Hierarchical Divergence Loss
Andong Lu, Chenglong Li, Yuqing Yan +2
RGBT tracking has attracted increasing attention since RGB and thermal infrared data have strong complementary advantages, which could make trackers all-day and all-weather work. H…
Duality-Gated Mutual Condition Network for RGBT Tracking
Andong Lu, Cun Qian, Chenglong Li +2
Low-quality modalities contain not only a lot of noisy information but also some discriminative features in RGBT tracking. However, the potentials of low-quality modalities are not…
Challenge-Aware RGBT Tracking
Chenglong Li, Lei Liu, Andong Lu +2
RGB and thermal source data suffer from both shared and specific challenges, and how to explore and exploit them plays a critical role to represent the target appearance in RGBT tr…
All at Once: Temporally Adaptive Multi-Frame Interpolation with Advanced Motion Modeling
Zhixiang Chi, Rasoul Mohammadi Nasiri, Zheng Liu +3
Recent advances in high refresh rate displays as well as the increased interest in high rate of slow motion and frame up-conversion fuel the demand for efficient and cost-effective…
Reversible data hiding in encrypted images based on pixel prediction and multi-MSB planes rearrangement
Zhaoxia Yin, Xiaomeng She, Jin Tang +1
Great concern has arisen in the field of reversible data hiding in encrypted images (RDHEI) due to the development of cloud storage and privacy protection. RDHEI is an effective te…
Multi-interactive Dual-decoder for RGB-thermal Salient Object Detection
Zhengzheng Tu, Zhun Li, Chenglong Li +2
RGB-thermal salient object detection (SOD) aims to segment the common prominent regions of visible image and corresponding thermal infrared image that we call it RGBT SOD. Existing…
SCRDet++: Detecting Small, Cluttered and Rotated Objects via Instance-Level Feature Denoising and Rotation Loss Smoothing
Xue Yang, Junchi Yan, Wenlong Liao +3
Small and cluttered objects are common in real-world which are challenging for detection. The difficulty is further pronounced when the objects are rotated, as traditional detector…
ML: Multi-Modal Multi-Margin Metric Learning for RGBT Tracking
Zhengzheng Tu, Chun Lin, Chenglong Li +2
Classifying the confusing samples in the course of RGBT tracking is a quite challenging problem, which hasn't got satisfied solution. Existing methods only focus on enlarging the b…
FMT:Fusing Multi-task Convolutional Neural Network for Person Search
Sulan Zhai, Shunqiang Liu, Xiao Wang +1
Person search is to detect all persons and identify the query persons from detected persons in the image without proposals and bounding boxes, which is different from person re-ide…
\emph{cm}SalGAN: RGB-D Salient Object Detection with Cross-View Generative Adversarial Networks
Bo Jiang, Zitai Zhou, Xiao Wang +2
Image salient object detection (SOD) is an active research topic in computer vision and multimedia area. Fusing complementary information of RGB and depth has been demonstrated to…
AttKGCN: Attribute Knowledge Graph Convolutional Network for Person Re-identification
Bo Jiang, Xixi Wang, Jin Tang
Discriminative feature representation of person image is important for person re-identification (Re-ID) task. Recently, attributes have been demonstrated beneficially in guiding fo…
GmCN: Graph Mask Convolutional Network
Bo Jiang, Beibei Wang, Jin Tang +1
Graph Convolutional Networks (GCNs) have shown very powerful for graph data representation and learning tasks. Existing GCNs usually conduct feature aggregation on a fixed neighbor…
GLMNet: Graph Learning-Matching Networks for Feature Matching
Bo Jiang, Pengfei Sun, Jin Tang +1
Recently, graph convolutional networks (GCNs) have shown great potential for the task of graph matching. It can integrate graph node feature embedding, node-wise affinity learning…
Context-Aware Graph Attention Networks
Bo Jiang, Leiling Wang, Jin Tang +1
Graph Neural Networks (GNNs) have been widely studied for graph data representation and learning. However, existing GNNs generally conduct context-aware learning on node feature re…