activity
20162026
most citedDeep Supervised Discrete Hashing

162 citations · 299 across the 19 of their papers we have counts for

collaborators

21 papers

cs.CV2026

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…

cs.CV2026

Primitive-Driven Compositional Forensic Visual Prompting for Open-World Face Anti-Spoofing

Fangling Jiang, Qi Li, Bing Liu +4

Open-world face anti-spoofing must address both covariate and semantic shifts: source and target domains differ in imaging conditions, while target domains contain diverse attack t…

cs.CV2026

AGC: Adaptive Geodesic Correction for Adversarial Robustness on Vision-Language Models

Zhiwei Li, Jiacheng Xue, Weining Wang +4

Vision-language models like CLIP have demonstrated remarkable zero-shot transfer capabilities. However, their susceptibility to imperceptible adversarial perturbations remains a cr…

cs.CV2026

Towards High Fidelity Face Swapping: A Comprehensive Survey and New Benchmark

Qi Li, Weining Wang, Shuangjun Du +5

Face swapping has witnessed significant progress in recent years, largely driven by advances in deep generative models such as GANs and diffusion models.Despite these advances, exi…

cs.CV2025

Exploring Task-Solving Paradigm for Generalized Cross-Domain Face Anti-Spoofing via Reinforcement Fine-Tuning

Fangling Jiang, Qi Li, Weining Wang +3

Recently the emergence of novel presentation attacks has drawn increasing attention to face anti-spoofing. However, existing methods tend to memorize data patterns from the trainin…

cs.CV2025

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…