activity
20232025
most citedIFViT: Interpretable Fixed-Length Representation for Fingerprint Matching via Vision Transformer

7 citations · 7 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CV2025

Unbiased Video Scene Graph Generation via Visual and Semantic Dual Debiasing

Yanjun Li, Zhaoyang Li, Honghui Chen +1

Video Scene Graph Generation (VidSGG) aims to capture dynamic relationships among entities by sequentially analyzing video frames and integrating visual and semantic information. H…

cs.RO2024

Optimizing Drug Delivery in Smart Pharmacies: A Novel Framework of Multi-Stage Grasping Network Combined with Adaptive Robotics Mechanism

Rui Tang, Shirong Guo, Yuhang Qiu +5

Robots-based smart pharmacies are essential for modern healthcare systems, enabling efficient drug delivery. However, a critical challenge exists in the robotic handling of drugs w…

cs.CV2024

A Hierarchically Feature Reconstructed Autoencoder for Unsupervised Anomaly Detection

Honghui Chen, Pingping Chen, Huan Mao +1

Anomaly detection and localization without any manual annotations and prior knowledge is a challenging task under the setting of unsupervised learning. The existing works achieve e…

cs.CV2024

HAAP: Vision-context Hierarchical Attention Autoregressive with Adaptive Permutation for Scene Text Recognition

Honghui Chen, Yuhang Qiu, Jiabao Wang +2

Scene Text Recognition (STR) is challenging in extracting effective character representations from visual data when text is unreadable. Permutation language modeling (PLM) is intro…

cs.CV2024★ 7 cited

IFViT: Interpretable Fixed-Length Representation for Fingerprint Matching via Vision Transformer

Yuhang Qiu, Honghui Chen, Xingbo Dong +4

Determining dense feature points on fingerprints used in constructing deep fixed-length representations for accurate matching, particularly at the pixel level, is of significant in…

cs.CV2023

Multiresolution Feature Guidance Based Transformer for Anomaly Detection

Shuting Yan, Pingping Chen, Honghui Chen +3

Anomaly detection is represented as an unsupervised learning to identify deviated images from normal images. In general, there are two main challenges of anomaly detection tasks, i…