Search Results for author: Shumin Han

Found 15 papers, 6 papers with code

Representation Disentanglement in Generative Models with Contrastive Learning

no code implementations29 Sep 2021 Shentong Mo, Zhun Sun, Shumin Han

Recent works apply the contrastive learning on the discriminator of the Generative Adversarial Networks, and there exists little work on exploring if contrastive learning can be applied on encoders to learn disentangled representations.

Contrastive Learning Disentanglement +1

Piecing and Chipping: An effective solution for the information-erasing view generation in Self-supervised Learning

no code implementations29 Sep 2021 Jingwei Liu, Yi Gu, Shentong Mo, Zhun Sun, Shumin Han, Jiafeng Guo, Xueqi Cheng

In self-supervised learning frameworks, deep networks are optimized to align different views of an instance that contains the similar visual semantic information.

Data Augmentation Self-Supervised Learning

Layer-Wise Searching for 1-Bit Detectors

no code implementations CVPR 2021 Sheng Xu, Junhe Zhao, Jinhu Lu, Baochang Zhang, Shumin Han, David Doermann

At each layer, it exploits a differentiable binarization search (DBS) to minimize the angular error in a student-teacher framework.

Binarization

Oriented Object Detection with Transformer

no code implementations6 Jun 2021 Teli Ma, Mingyuan Mao, Honghui Zheng, Peng Gao, Xiaodi Wang, Shumin Han, Errui Ding, Baochang Zhang, David Doermann

Object detection with Transformers (DETR) has achieved a competitive performance over traditional detectors, such as Faster R-CNN.

Object Detection

Dual-stream Network for Visual Recognition

no code implementations NeurIPS 2021 Mingyuan Mao, Renrui Zhang, Honghui Zheng, Peng Gao, Teli Ma, Yan Peng, Errui Ding, Baochang Zhang, Shumin Han

Transformers with remarkable global representation capacities achieve competitive results for visual tasks, but fail to consider high-level local pattern information in input images.

Image Classification Instance Segmentation +2

PAFNet: An Efficient Anchor-Free Object Detector Guidance

1 code implementation28 Apr 2021 Ying Xin, Guanzhong Wang, Mingyuan Mao, Yuan Feng, Qingqing Dang, Yanjun Ma, Errui Ding, Shumin Han

Therefore, a trade-off between effectiveness and efficiency is necessary in practical scenarios.

 Ranked #1 on Object Detection on COCO test-dev (Hardware Burden metric)

Object Detection

PP-YOLOv2: A Practical Object Detector

1 code implementation21 Apr 2021 Xin Huang, Xinxin Wang, Wenyu Lv, Xiaying Bai, Xiang Long, Kaipeng Deng, Qingqing Dang, Shumin Han, Qiwen Liu, Xiaoguang Hu, dianhai yu, Yanjun Ma, Osamu Yoshie

To meet these two concerns, we comprehensively evaluate a collection of existing refinements to improve the performance of PP-YOLO while almost keep the infer time unchanged.

Student-Teacher Feature Pyramid Matching for Anomaly Detection

5 code implementations7 Mar 2021 Guodong Wang, Shumin Han, Errui Ding, Di Huang

Anomaly detection is a challenging task and usually formulated as an one-class learning problem for the unexpectedness of anomalies.

Ranked #17 on Anomaly Detection on MVTec AD (using extra training data)

Image Classification Unsupervised Anomaly Detection

HS-ResNet: Hierarchical-Split Block on Convolutional Neural Network

2 code implementations15 Oct 2020 Pengcheng Yuan, Shufei Lin, Cheng Cui, Yuning Du, Ruoyu Guo, Dongliang He, Errui Ding, Shumin Han

Moreover, Hierarchical-Split block is very flexible and efficient, which provides a large space of potential network architectures for different applications.

Image Classification Instance Segmentation +2

The 1st Tiny Object Detection Challenge:Methods and Results

1 code implementation16 Sep 2020 Xuehui Yu, Zhenjun Han, Yuqi Gong, Nan Jiang, Jian Zhao, Qixiang Ye, Jie Chen, Yuan Feng, Bin Zhang, Xiaodi Wang, Ying Xin, Jingwei Liu, Mingyuan Mao, Sheng Xu, Baochang Zhang, Shumin Han, Cheng Gao, Wei Tang, Lizuo Jin, Mingbo Hong, Yuchao Yang, Shuiwang Li, Huan Luo, Qijun Zhao, Humphrey Shi

The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.

Human Detection Object Detection

PP-YOLO: An Effective and Efficient Implementation of Object Detector

5 code implementations23 Jul 2020 Xiang Long, Kaipeng Deng, Guanzhong Wang, Yang Zhang, Qingqing Dang, Yuan Gao, Hui Shen, Jianguo Ren, Shumin Han, Errui Ding, Shilei Wen

We mainly try to combine various existing tricks that almost not increase the number of model parameters and FLOPs, to achieve the goal of improving the accuracy of detector as much as possible while ensuring that the speed is almost unchanged.

Object Detection

Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification

no code implementations2 Nov 2018 Jia Li, Yafei Song, Jianfeng Zhu, Lele Cheng, Ying Su, Lin Ye, Pengcheng Yuan, Shumin Han

In this manner, the influence of bias and noise in the web data can be gradually alleviated, leading to the steadily improving performance of URNet.

General Classification Image Classification

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