363 citations · 897 across the 14 of their papers we have counts for
11 papers · 1 filter
Illumination Distillation Framework for Nighttime Person Re-Identification and A New Benchmark
Andong Lu, Zhang Zhang, Yan Huang +4
Nighttime person Re-ID (person re-identification in the nighttime) is a very important and challenging task for visual surveillance but it has not been thoroughly investigated. Und…
Semantic Prompt for Few-Shot Image Recognition
Wentao Chen, Chenyang Si, Zhang Zhang +3
Few-shot learning is a challenging problem since only a few examples are provided to recognize a new class. Several recent studies exploit additional semantic information, e.g. tex…
Human Image Generation: A Comprehensive Survey
Zhen Jia, Zhang Zhang, Liang Wang +1
Image and video synthesis has become a blooming topic in computer vision and machine learning communities along with the developments of deep generative models, due to its great ac…
Constructing Stronger and Faster Baselines for Skeleton-based Action Recognition
Yi-Fan Song, Zhang Zhang, Caifeng Shan +1
One essential problem in skeleton-based action recognition is how to extract discriminative features over all skeleton joints. However, the complexity of the recent State-Of-The-Ar…
Learning Domain Invariant Representations for Generalizable Person Re-Identification
Yi-Fan Zhang, Zhang Zhang, Da Li +3
Generalizable person Re-Identification (ReID) has attracted growing attention in recent computer vision community. In this work, we construct a structural causal model among identi…
Focal and Efficient IOU Loss for Accurate Bounding Box Regression
Yi-Fan Zhang, Weiqiang Ren, Zhang Zhang +3
In object detection, bounding box regression (BBR) is a crucial step that determines the object localization performance. However, we find that most previous loss functions for BBR…
Stronger, Faster and More Explainable: A Graph Convolutional Baseline for Skeleton-based Action Recognition
Yi-Fan Song, Zhang Zhang, Caifeng Shan +1
One essential problem in skeleton-based action recognition is how to extract discriminative features over all skeleton joints. However, the complexity of the State-Of-The-Art (SOTA…
Richly Activated Graph Convolutional Network for Robust Skeleton-based Action Recognition
Yi-Fan Song, Zhang Zhang, Caifeng Shan +1
Current methods for skeleton-based human action recognition usually work with complete skeletons. However, in real scenarios, it is inevitable to capture incomplete or noisy skelet…
Richly Activated Graph Convolutional Network for Action Recognition with Incomplete Skeletons
Yi-Fan Song, Zhang Zhang, Liang Wang
Current methods for skeleton-based human action recognition usually work with completely observed skeletons. However, in real scenarios, it is prone to capture incomplete and noisy…
Large-Scale Pedestrian Retrieval Competition
Da Li, Zhang Zhang
The Large-Scale Pedestrian Retrieval Competition (LSPRC) mainly focuses on person retrieval which is an important end application in intelligent vision system of surveillance. Pers…
Weakly-supervised Learning of Mid-level Features for Pedestrian Attribute Recognition and Localization
Kai Yu, Biao Leng, Zhang Zhang +2
State-of-the-art methods treat pedestrian attribute recognition as a multi-label image classification problem. The location information of person attributes is usually eliminated o…