Search Results for author: Cheng Yan

Found 8 papers, 2 papers with code

Biomedical Concept Normalization by Leveraging Hypernyms

1 code implementation EMNLP 2021 Cheng Yan, Yuanzhe Zhang, Kang Liu, Jun Zhao, Yafei Shi, Shengping Liu

Biomedical Concept Normalization (BCN) is widely used in biomedical text processing as a fundamental module.

Occluded Person Re-Identification With Single-Scale Global Representations

no code implementations ICCV 2021 Cheng Yan, Guansong Pang, Jile Jiao, Xiao Bai, Xuetao Feng, Chunhua Shen

However, real-world ReID applications typically have highly diverse occlusions and involve a hybrid of occluded and non-occluded pedestrians.

Graph Matching Person Re-Identification +1

BV-Person: A Large-Scale Dataset for Bird-View Person Re-Identification

no code implementations ICCV 2021 Cheng Yan, Guansong Pang, Lei Wang, Jile Jiao, Xuetao Feng, Chunhua Shen, Jingjing Li

In this work we introduce a new ReID task, bird-view person ReID, which aims at searching for a person in a gallery of horizontal-view images with the query images taken from a bird's-eye view, i. e., an elevated view of an object from above.

Person Re-Identification

A New Action Recognition Framework for Video Highlights Summarization in Sporting Events

no code implementations1 Dec 2020 Cheng Yan, Xin Li, Guoqiang Li

To date, machine learning for human action recognition in video has been widely implemented in sports activities.

Action Recognition Video Summarization

Beyond Triplet Loss: Person Re-identification with Fine-grained Difference-aware Pairwise Loss

no code implementations22 Sep 2020 Cheng Yan, Guansong Pang, Xiao Bai, Jun Zhou, Lin Gu

The proposed loss is generic and can be used as a plugin to replace the triplet loss to significantly enhance different types of state-of-the-art approaches.

Person Re-Identification

Self-trained Deep Ordinal Regression for End-to-End Video Anomaly Detection

no code implementations CVPR 2020 Guansong Pang, Cheng Yan, Chunhua Shen, Anton Van Den Hengel, Xiao Bai

Video anomaly detection is of critical practical importance to a variety of real applications because it allows human attention to be focused on events that are likely to be of interest, in spite of an otherwise overwhelming volume of video.

Anomaly Detection Representation Learning

Unified Multifaceted Feature Learning for Person Re-Identification

no code implementations20 Nov 2019 Cheng Yan, Guansong Pang, Xiao Bai, Chunhua Shen

The loss structures the augmented images resulted by the two types of image erasing in a two-level hierarchy and enforces multifaceted attention to different parts.

Person Re-Identification

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