22 citations · 34 across the 11 of their papers we have counts for
12 papers
FVeinSyn: Synthetic Finger Vein Image Generator
Yifan Wang, Jie Gui, Adams Wai Kin Kong +6
A major challenge in finger vein recognition is the lack of large-scale public datasets. Existing datasets contain few identities and limited samples per finger, restricting the ad…
Affinity Contrastive Learning for Skeleton-based Human Activity Understanding
Hongda Liu, Yunfan Liu, Min Ren +3
In skeleton-based human activity understanding, existing methods often adopt the contrastive learning paradigm to construct a discriminative feature space. However, many of these a…
SkeletonAgent: An Agentic Interaction Framework for Skeleton-based Action Recognition
Hongda Liu, Yunfan Liu, Changlu Wang +2
Recent advances in skeleton-based action recognition increasingly leverage semantic priors from Large Language Models (LLMs) to enrich skeletal representations. However, the LLM is…
FingerVeinSyn-5M: A Million-Scale Dataset and Benchmark for Finger Vein Recognition
Yinfan Wang, Jie Gui, Baosheng Yu +4
A major challenge in finger vein recognition is the lack of large-scale public datasets. Existing datasets contain few identities and limited samples per finger, restricting the ad…
Revealing Key Details to See Differences: A Novel Prototypical Perspective for Skeleton-based Action Recognition
Hongda Liu, Yunfan Liu, Min Ren +3
In skeleton-based action recognition, a key challenge is distinguishing between actions with similar trajectories of joints due to the lack of image-level details in skeletal repre…
A Unified Framework for Iris Anti-Spoofing: Introducing Iris Anti-Spoofing Cross-Domain-Testing Protocol and Masked-MoE Method
Hang Zou, Chenxi Du, Ajian Liu +6
Iris recognition is widely used in high-security scenarios due to its stability and distinctiveness. However, iris images captured by different devices exhibit certain and device-r…
Balanced Representation Learning for Long-tailed Skeleton-based Action Recognition
Hongda Liu, Yunlong Wang, Min Ren +4
Skeleton-based action recognition has recently made significant progress. However, data imbalance is still a great challenge in real-world scenarios. The performance of current act…
A Survey on Self-supervised Learning: Algorithms, Applications, and Future Trends
Jie Gui, Tuo Chen, Jing Zhang +4
Deep supervised learning algorithms typically require a large volume of labeled data to achieve satisfactory performance. However, the process of collecting and labeling such data…
Deep Learning-based Occluded Person Re-identification: A Survey
Yunjie Peng, Saihui Hou, Chunshui Cao +3
Occluded person re-identification (Re-ID) aims at addressing the occlusion problem when retrieving the person of interest across multiple cameras. With the promotion of deep learni…
Exploring Generalizable Distillation for Efficient Medical Image Segmentation
Xingqun Qi, Zhuojie Wu, Min Ren +3
Efficient medical image segmentation aims to provide accurate pixel-wise predictions for medical images with a lightweight implementation framework. However, lightweight frameworks…
Graph Flow: Cross-layer Graph Flow Distillation for Dual Efficient Medical Image Segmentation
Wenxuan Zou, Muyi Sun
With the development of deep convolutional neural networks, medical image segmentation has achieved a series of breakthroughs in recent years. However, the high-performance convolu…
Mimic Embedding via Adaptive Aggregation: Learning Generalizable Person Re-identification
Boqiang Xu, Jian Liang, Lingxiao He +1
Domain generalizable (DG) person re-identification (ReID) aims to test across unseen domains without access to the target domain data at training time, which is a realistic but cha…