Search Results for author: Annan Li

Found 14 papers, 6 papers with code

RealGait: Gait Recognition for Person Re-Identification

1 code implementation13 Jan 2022 Shaoxiong Zhang, Yunhong Wang, Tianrui Chai, Annan Li, Anil K. Jain

Given that our experimental results show that current gait recognition approaches designed under data collected in controlled scenarios are inappropriate for real surveillance scenarios, we propose a novel gait recognition method, called RealGait.

Gait Recognition Person Recognition +1

Will You Ever Become Popular? Learning to Predict Virality of Dance Clips

no code implementations6 Nov 2021 Jiahao Wang, Yunhong Wang, Nina Weng, Tianrui Chai, Annan Li, Faxi Zhang, Sansi Yu

Therefore, virality prediction from dance challenges is of great commercial value and has a wide range of applications, such as smart recommendation and popularity promotion.

Video Person Re-identification using Attribute-enhanced Features

no code implementations16 Aug 2021 Tianrui Chai, ZhiYuan Chen, Annan Li, Jiaxin Chen, Xinyu Mei, Yunhong Wang

Video-based person re-identification (Re-ID) which aims to associate people across non-overlapping cameras using surveillance video is a challenging task.

Video-Based Person Re-Identification

Few-Shot Fine-Grained Action Recognition via Bidirectional Attention and Contrastive Meta-Learning

1 code implementation15 Aug 2021 Jiahao Wang, Yunhong Wang, Sheng Liu, Annan Li

Fine-grained action recognition is attracting increasing attention due to the emerging demand of specific action understanding in real-world applications, whereas the data of rare fine-grained categories is very limited.

Action Understanding Fine-grained Action Recognition +1

Silhouette based View embeddings for Gait Recognition under Multiple Views

1 code implementation12 Aug 2021 Tianrui Chai, Xinyu Mei, Annan Li, Yunhong Wang

Gait recognition under multiple views is an important computer vision and pattern recognition task.

Gait Recognition

Cross-View Gait Recognition With Deep Universal Linear Embeddings

no code implementations CVPR 2021 Shaoxiong Zhang, Yunhong Wang, Annan Li

Furthermore, a novel framework based on convolutional variational autoencoder and deep Koopman embedding is proposed to approximate the Koopman operators, which is used as dynamical features from the linearized embedding space for cross-view gait recognition.

Gait Recognition

ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement Modeling

1 code implementation SEMEVAL 2020 Yaojie Lu, Annan Li, Hongyu Lin, Xianpei Han, Le Sun

ISCAS participated in two subtasks of SemEval 2020 Task 5: detecting counterfactual statements and detecting antecedent and consequence.

Question Answering

A Temporal Attentive Approach for Video-Based Pedestrian Attribute Recognition

no code implementations17 Jan 2019 Zhiyuan Chen, Annan Li, Yunhong Wang

In this paper, we first tackle the problem of pedestrian attribute recognition by video-based approach.

Pedestrian Attribute Recognition

stagNet: An Attentive Semantic RNN for Group Activity Recognition

no code implementations ECCV 2018 Mengshi Qi, Jie Qin, Annan Li, Yunhong Wang, Jiebo Luo, Luc van Gool

Group activity recognition plays a fundamental role in a variety of applications, e. g. sports video analysis and intelligent surveillance.

Group Activity Recognition

Adversarial Binary Coding for Efficient Person Re-identification

no code implementations29 Mar 2018 Zheng Liu, Jie Qin, Annan Li, Yunhong Wang, Luc van Gool

Specifically, instead of learning explicit projections or adding fully-connected mapping layers, the proposed Adversarial Binary Coding (ABC) framework guides the extraction of binary codes implicitly and effectively.

Person Re-Identification

Cross-pose Face Recognition by Canonical Correlation Analysis

no code implementations29 Jul 2015 Annan Li, Shiguang Shan, Xilin Chen, Bingpeng Ma, Shuicheng Yan, Wen Gao

We argue that one of the diffculties in this problem is the severe misalignment in face images or feature vectors with different poses.

Face Recognition

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