343 citations · 508 across the 13 of their papers we have counts for
13 papers · 1 filter
Erasing, Transforming, and Noising Defense Network for Occluded Person Re-Identification
Neng Dong, Liyan Zhang, Shuanglin Yan +2
Occlusion perturbation presents a significant challenge in person re-identification (re-ID), and existing methods that rely on external visual cues require additional computational…
Coupling Global Context and Local Contents for Weakly-Supervised Semantic Segmentation
Chunyan Wang, Dong Zhang, Liyan Zhang +1
Thanks to the advantages of the friendly annotations and the satisfactory performance, Weakly-Supervised Semantic Segmentation (WSSS) approaches have been extensively studied. Rece…
Triplet Contrastive Representation Learning for Unsupervised Vehicle Re-identification
Fei Shen, Xiaoyu Du, Liyan Zhang +2
Part feature learning is critical for fine-grained semantic understanding in vehicle re-identification. However, existing approaches directly model part features and global feature…
CLIP-Driven Fine-grained Text-Image Person Re-identification
Shuanglin Yan, Neng Dong, Liyan Zhang +1
TIReID aims to retrieve the image corresponding to the given text query from a pool of candidate images. Existing methods employ prior knowledge from single-modality pre-training t…
Centralized Feature Pyramid for Object Detection
Yu Quan, Dong Zhang, Liyan Zhang +1
Visual feature pyramid has shown its superiority in both effectiveness and efficiency in a wide range of applications. However, the existing methods exorbitantly concentrate on the…
Image-Specific Information Suppression and Implicit Local Alignment for Text-based Person Search
Shuanglin Yan, Hao Tang, Liyan Zhang +1
Text-based person search (TBPS) is a challenging task that aims to search pedestrian images with the same identity from an image gallery given a query text. In recent years, TBPS h…
Semantically Contrastive Learning for Low-light Image Enhancement
Dong Liang, Ling Li, Mingqiang Wei +5
Low-light image enhancement (LLE) remains challenging due to the unfavorable prevailing low-contrast and weak-visibility problems of single RGB images. In this paper, we respond to…
CTNet: Context-based Tandem Network for Semantic Segmentation
Zechao Li, Yanpeng Sun, Jinhui Tang
Contextual information has been shown to be powerful for semantic segmentation. This work proposes a novel Context-based Tandem Network (CTNet) by interactively exploring the spati…
Learning Calibrated-Guidance for Object Detection in Aerial Images
Zongqi Wei, Dong Liang, Dong Zhang +4
Object detection is one of the most fundamental yet challenging research topics in the domain of computer vision. Recently, the study on this topic in aerial images has made tremen…
Graph Attention Tracking
Dongyan Guo, Yanyan Shao, Ying Cui +3
Siamese network based trackers formulate the visual tracking task as a similarity matching problem. Almost all popular Siamese trackers realize the similarity learning via convolut…
Spatiotemporal Co-attention Recurrent Neural Networks for Human-Skeleton Motion Prediction
Xiangbo Shu, Liyan Zhang, Guo-Jun Qi +2
Human motion prediction aims to generate future motions based on the observed human motions. Witnessing the success of Recurrent Neural Networks (RNN) in modeling the sequential da…
Personalized Age Progression with Bi-level Aging Dictionary Learning
Xiangbo Shu, Jinhui Tang, Zechao Li +3
Age progression is defined as aesthetically re-rendering the aging face at any future age for an individual face. In this work, we aim to automatically render aging faces in a pers…
Concurrence-Aware Long Short-Term Sub-Memories for Person-Person Action Recognition
Xiangbo Shu
Recently, Long Short-Term Memory (LSTM) has become a popular choice to model individual dynamics for single-person action recognition due to its ability of modeling the temporal in…