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20172022
most citedNoisy Softmax: Improving the Generalization Ability of DCNN via Postponing the Early Softmax Saturation

30 citations · 46 across the 6 of their papers we have counts for

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11 papers · 1 filter

cs.CV20221 cited

Learning Polysemantic Spoof Trace: A Multi-Modal Disentanglement Network for Face Anti-spoofing

Kaicheng Li, Hongyu Yang, Binghui Chen +3

Along with the widespread use of face recognition systems, their vulnerability has become highlighted. While existing face anti-spoofing methods can be generalized between attack t…

cs.CV20225 cited

Dense Learning based Semi-Supervised Object Detection

Binghui Chen, Pengyu Li, Xiang Chen +3

Semi-supervised object detection (SSOD) aims to facilitate the training and deployment of object detectors with the help of a large amount of unlabeled data. Though various self-tr…

cs.CV2021

Variational Attention: Propagating Domain-Specific Knowledge for Multi-Domain Learning in Crowd Counting

Binghui Chen, Zhaoyi Yan, Ke Li +4

In crowd counting, due to the problem of laborious labelling, it is perceived intractability of collecting a new large-scale dataset which has plentiful images with large diversity…

cs.CV2019

Mixed High-Order Attention Network for Person Re-Identification

Binghui Chen, Weihong Deng, Jiani Hu

Attention has become more attractive in person reidentification (ReID) as it is capable of biasing the allocation of available resources towards the most informative parts of an in…

cs.CV2019

Hybrid-Attention based Decoupled Metric Learning for Zero-Shot Image Retrieval

Binghui Chen, Weihong Deng

In zero-shot image retrieval (ZSIR) task, embedding learning becomes more attractive, however, many methods follow the traditional metric learning idea and omit the problems behind…

cs.CV20196 cited

Signal-to-Noise Ratio: A Robust Distance Metric for Deep Metric Learning

Tongtong Yuan, Weihong Deng, Jian Tang +2

Deep metric learning, which learns discriminative features to process image clustering and retrieval tasks, has attracted extensive attention in recent years. A number of deep metr…