activity
20152020
most citedWasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition

29 citations · 86 across the 8 of their papers we have counts for

collaborators

14 papers

cs.CV2020

Imbalance Robust Softmax for Deep Embeeding Learning

Hao Zhu, Yang Yuan, Guosheng Hu +2

Deep embedding learning is expected to learn a metric space in which features have smaller maximal intra-class distance than minimal inter-class distance. In recent years, one rese…

cs.CV2020

DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition

Chaoyou Fu, Xiang Wu, Yibo Hu +2

Heterogeneous Face Recognition (HFR) refers to matching cross-domain faces and plays a crucial role in public security. Nevertheless, HFR is confronted with challenges from large d…

cs.CV20208 cited

TF-NAS: Rethinking Three Search Freedoms of Latency-Constrained Differentiable Neural Architecture Search

Yibo Hu, Xiang Wu, Ran He

With the flourish of differentiable neural architecture search (NAS), automatically searching latency-constrained architectures gives a new perspective to reduce human labor and ex…

cs.CV201916 cited

HAMBox: Delving into Online High-quality Anchors Mining for Detecting Outer Faces

Yang Liu, Xu Tang, Xiang Wu +3

Current face detectors utilize anchors to frame a multi-task learning problem which combines classification and bounding box regression. Effective anchor design and anchor matching…

cs.CV2019

M2FPA: A Multi-Yaw Multi-Pitch High-Quality Database and Benchmark for Facial Pose Analysis

Peipei Li, Xiang Wu, Yibo Hu +2

Facial images in surveillance or mobile scenarios often have large view-point variations in terms of pitch and yaw angles. These jointly occurred angle variations make face recogni…

cs.CV20193 cited

UVA: A Universal Variational Framework for Continuous Age Analysis

Peipei Li, Huaibo Huang, Yibo Hu +3

Conventional methods for facial age analysis tend to utilize accurate age labels in a supervised way. However, existing age datasets lies in a limited range of ages, leading to a l…