activity
20192026
most citedOutfit Compatibility Prediction and Diagnosis with Multi-Layered Comparison Network

44 citations · 114 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CV2026

GigaWorld-Policy: An Efficient Action-Centered World--Action Model

Angen Ye, Boyuan Wang, Chaojun Ni +21

World-Action Models (WAM) initialized from pre-trained video generation backbones have demonstrated remarkable potential for robot policy learning. However, existing approaches fac…

cs.CV2022★ 1 cited

WebFace260M: A Benchmark for Million-Scale Deep Face Recognition

Zheng Zhu, Guan Huang, Jiankang Deng +8

Face benchmarks empower the research community to train and evaluate high-performance face recognition systems. In this paper, we contribute a new million-scale recognition benchma…

cs.CV2021★ 24 cited

Masked Face Recognition Challenge: The WebFace260M Track Report

Zheng Zhu, Guan Huang, Jiankang Deng +9

According to WHO statistics, there are more than 204,617,027 confirmed COVID-19 cases including 4,323,247 deaths worldwide till August 12, 2021. During the coronavirus epidemic, al…

cs.CV2021★ 24 cited

WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition

Zheng Zhu, Guan Huang, Jiankang Deng +8

In this paper, we contribute a new million-scale face benchmark containing noisy 4M identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) training da…

cs.CV2020★ 1 cited

MFPP: Morphological Fragmental Perturbation Pyramid for Black-Box Model Explanations

Qing Yang, Xia Zhu, Jong-Kae Fwu +3

Deep neural networks (DNNs) have recently been applied and used in many advanced and diverse tasks, such as medical diagnosis, automatic driving, etc. Due to the lack of transparen…

cs.CV2020★ 1 cited

PipeNet: Selective Modal Pipeline of Fusion Network for Multi-Modal Face Anti-Spoofing

Qing Yang, Xia Zhu, Jong-Kae Fwu +3

Face anti-spoofing has become an increasingly important and critical security feature for authentication systems, due to rampant and easily launchable presentation attacks. Address…