activity
20172019
most citedNoisy Softmax: Improving the Generalization Ability of DCNN via Postponing the Early Softmax Saturation

30 citations · 40 across the 3 of their papers we have counts for

collaborators

6 papers

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…

cs.CV20194 cited

Energy Confused Adversarial Metric Learning for Zero-Shot Image Retrieval and Clustering

Binghui Chen, Weihong Deng

Deep metric learning has been widely applied in many computer vision tasks, and recently, it is more attractive in \emph{zero-shot image retrieval and clustering}(ZSRC) where a goo…

cs.CV2018

Virtual Class Enhanced Discriminative Embedding Learning

Binghui Chen, Weihong Deng, Haifeng Shen

Recently, learning discriminative features to improve the recognition performances gradually becomes the primary goal of deep learning, and numerous remarkable works have emerged.…

cs.CV201730 cited

Noisy Softmax: Improving the Generalization Ability of DCNN via Postponing the Early Softmax Saturation

Binghui Chen, Weihong Deng, Junping Du

Over the past few years, softmax and SGD have become a commonly used component and the default training strategy in CNN frameworks, respectively. However, when optimizing CNNs with…