Search Results for author: Binghui Chen

Found 15 papers, 6 papers with code

DAMO-StreamNet: Optimizing Streaming Perception in Autonomous Driving

1 code implementation30 Mar 2023 Jun-Yan He, Zhi-Qi Cheng, Chenyang Li, Wangmeng Xiang, Binghui Chen, Bin Luo, Yifeng Geng, Xuansong Xie

Real-time perception, or streaming perception, is a crucial aspect of autonomous driving that has yet to be thoroughly explored in existing research.

Autonomous Driving

Optimal Proposal Learning for Deployable End-to-End Pedestrian Detection

no code implementations CVPR 2023 Xiaolin Song, Binghui Chen, Pengyu Li, Jun-Yan He, Biao Wang, Yifeng Geng, Xuansong Xie, Honggang Zhang

End-to-end pedestrian detection focuses on training a pedestrian detection model via discarding the Non-Maximum Suppression (NMS) post-processing.

Pedestrian Detection

Dense Learning based Semi-Supervised Object Detection

1 code implementation CVPR 2022 Binghui Chen, Pengyu Li, Xiang Chen, Biao Wang, Lei Zhang, Xian-Sheng Hua

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.

object-detection Object Detection +1

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

1 code implementation ICCV 2021 Binghui Chen, Zhaoyi Yan, Ke Li, Pengyu Li, Biao Wang, WangMeng Zuo, Lei Zhang

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 in density, scene, etc.

Crowd Counting

VirFace: Enhancing Face Recognition via Unlabeled Shallow Data

no code implementations CVPR 2021 Wenyu Li, Tianchu Guo, Pengyu Li, Binghui Chen, Biao Wang, WangMeng Zuo, Lei Zhang

In this paper, we propose a novel face recognition method, named VirFace, to effectively apply the unlabeled shallow data for face recognition.

Face Recognition

MedSRGAN: medical images super-resolution using generative adversarial networks

1 code implementation Springer 2020 Yuchong Gu, Zitao Zen, Haibin Chen, Jun Wei, Yaqin Zhang, Binghui Chen, Yingqin Li, Yujuan Qin, Qing Xie, Zhuoren Jiang, Yao Lu

Super-resolution (SR) in medical imaging is an emerging application in medical imaging due to the needs of high quality images acquired with limited radiation dose, such as low dose Computer Tomography (CT), low field magnetic resonance imaging (MRI).


Mixed High-Order Attention Network for Person Re-Identification

1 code implementation ICCV 2019 Binghui Chen, Weihong Deng, Jiani Hu

Then, rethinking person ReID as a zero-shot learning problem, we propose the Mixed High-Order Attention Network (MHN) to further enhance the discrimination and richness of attention knowledge in an explicit manner.

Person Re-Identification Vocal Bursts Intensity Prediction +1

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

no code implementations CVPR 2019 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 zero-shot settings.

Image Retrieval Metric Learning +2

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

no code implementations CVPR 2019 Tongtong Yuan, Weihong Deng, Jian Tang, Yinan Tang, Binghui Chen

In this paper, different from the approaches on learning the loss structures, we propose a robust SNR distance metric based on Signal-to-Noise Ratio (SNR) for measuring the similarity of image pairs for deep metric learning.

Image Clustering Metric Learning +3

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

no code implementations22 Jan 2019 Binghui Chen, Weihong Deng

However, in this paper, we first emphasize that the generalization ability is a core ingredient of this 'good' embedding as well and largely affects the metric performance in zero-shot settings as a matter of fact.

Image Retrieval Metric Learning +2

Virtual Class Enhanced Discriminative Embedding Learning

1 code implementation NeurIPS 2018 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.

Face Verification General Classification

Learning Better Features for Face Detection with Feature Fusion and Segmentation Supervision

no code implementations20 Nov 2018 Wanxin Tian, Zixuan Wang, Haifeng Shen, Weihong Deng, Yiping Meng, Binghui Chen, Xiubao Zhang, Yuan Zhao, Xiehe Huang

We assume that problems inside are inadequate use of supervision information and imbalance between semantics and details at all level feature maps in CNN even with Feature Pyramid Networks (FPN).

Face Detection Semantic Segmentation

ALMN: Deep Embedding Learning with Geometrical Virtual Point Generating

no code implementations4 Jun 2018 Binghui Chen, Weihong Deng

Deep embedding learning becomes more attractive for discriminative feature learning, but many methods still require hard-class mining, which is computationally complex and performance-sensitive.

Image Retrieval Retrieval

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

no code implementations CVPR 2017 Binghui Chen, Weihong Deng, Junping Du

In this paper, we first emphasize that the early saturation behavior of softmax will impede the exploration of SGD, which sometimes is a reason for model converging at a bad local-minima, then propose Noisy Softmax to mitigating this early saturation issue by injecting annealed noise in softmax during each iteration.

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