109 citations · 303 across the 11 of their papers we have counts for
7 papers · 1 filter
Spherical Feature Transform for Deep Metric Learning
Yuke Zhu, Yan Bai, Yichen Wei
Data augmentation in feature space is effective to increase data diversity. Previous methods assume that different classes have the same covariance in their feature distributions.…
Prime-Aware Adaptive Distillation
Youcai Zhang, Zhonghao Lan, Yuchen Dai +4
Knowledge distillation(KD) aims to improve the performance of a student network by mimicing the knowledge from a powerful teacher network. Existing methods focus on studying what k…
Angle-based Search Space Shrinking for Neural Architecture Search
Yiming Hu, Yuding Liang, Zichao Guo +5
In this work, we present a simple and general search space shrinking method, called Angle-Based search space Shrinking (ABS), for Neural Architecture Search (NAS). Our approach pro…
Data Uncertainty Learning in Face Recognition
Jie Chang, Zhonghao Lan, Changmao Cheng +1
Modeling data uncertainty is important for noisy images, but seldom explored for face recognition. The pioneer work, PFE, considers uncertainty by modeling each face image embeddin…
Balanced Alignment for Face Recognition: A Joint Learning Approach
Huawei Wei, Peng Lu, Yichen Wei
Face alignment is crucial for face recognition and has been widely adopted. However, current practice is too simple and under-explored. There lacks an understanding of how importan…
Circle Loss: A Unified Perspective of Pair Similarity Optimization
Yifan Sun, Changmao Cheng, Yuhan Zhang +4
This paper provides a pair similarity optimization viewpoint on deep feature learning, aiming to maximize the within-class similarity and minimize the between-class similarit…