activity
20162026
most citedNAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofing

270 citations · 605 across the 28 of their papers we have counts for

collaborators
Showing 2023Show all

7 papers · 1 filter

cs.CV2023★ 8 cited

Gloss-free Sign Language Translation: Improving from Visual-Language Pretraining

Benjia Zhou, Zhigang Chen, Albert Clapés +5

Sign Language Translation (SLT) is a challenging task due to its cross-domain nature, involving the translation of visual-gestural language to text. Many previous methods employ an…

cs.CV2023

General vs. Long-Tailed Age Estimation: An Approach to Kill Two Birds with One Stone

Zenghao Bao, Zichang Tan, Jun Li +3

Facial age estimation has received a lot of attention for its diverse application scenarios. Most existing studies treat each sample equally and aim to reduce the average estimatio…

cs.CV2023★ 1 cited

NCL++: Nested Collaborative Learning for Long-Tailed Visual Recognition

Zichang Tan, Jun Li, Jinhao Du +3

Long-tailed visual recognition has received increasing attention in recent years. Due to the extremely imbalanced data distribution in long-tailed learning, the learning process sh…

cs.CV2023★ 4 cited

FM-ViT: Flexible Modal Vision Transformers for Face Anti-Spoofing

Ajian Liu, Zichang Tan, Zitong Yu +7

The availability of handy multi-modal (i.e., RGB-D) sensors has brought about a surge of face anti-spoofing research. However, the current multi-modal face presentation attack dete…

cs.CV2023★ 1 cited

Wild Face Anti-Spoofing Challenge 2023: Benchmark and Results

Dong Wang, Jia Guo, Qiqi Shao +9

Face anti-spoofing (FAS) is an essential mechanism for safeguarding the integrity of automated face recognition systems. Despite substantial advancements, the generalization of exi…

cs.CV2023★ 5 cited

Surveillance Face Presentation Attack Detection Challenge

Hao Fang, Ajian Liu, Jun Wan +3

Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, most of the studies lacked consideration of long-distance scenarios…