1 code implementation • ECCV 2020 • Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang
Gait recognition aims at identifying different people by the walking patterns, which can be conducted at a long distance without the cooperation of subjects.
1 code implementation • 7 Mar 2024 • Qingyuan Cai, Xuecai Hu, Saihui Hou, Li Yao, Yongzhen Huang
To address these problems, a Disentangled Diffusion-based 3D Human Pose Estimation method with Hierarchical Spatial and Temporal Denoiser is proposed, termed DDHPose.
1 code implementation • 24 Jan 2024 • Zengbin Wang, Saihui Hou, Man Zhang, Xu Liu, Chunshui Cao, Yongzhen Huang, Peipei Li, Shibiao Xu
Gait recognition is a promising biometric method that aims to identify pedestrians from their unique walking patterns.
no code implementations • 10 Oct 2023 • Min Ren, Muchan Tao, Xuecai Hu, Xiaotong Liu, Qiong Li, Yongzhen Huang
Gait is a complex form of motion, and hand-crafted gait features often only capture a fraction of the intricate associations between gait and depression risk.
1 code implementation • 2 Sep 2023 • Shibei Meng, Yang Fu, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang
Our toolbox supports a set of cutting-edge pose-based gait recognition algorithms and a variety of related benchmarks.
no code implementations • 22 Aug 2023 • Jilong Wang, Saihui Hou, Yan Huang, Chunshui Cao, Xu Liu, Yongzhen Huang, Tianzhu Zhang, Liang Wang
Gait recognition is to seek correct matches for query individuals by their unique walking patterns.
no code implementations • 19 Mar 2023 • Xuqian Ren, Shaopeng Yang, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang
So to make the pre-trained gait recognition model able to be fine-tuned on unlabeled datasets, we propose a new task: Unsupervised Gait Recognition (UGR).
2 code implementations • ICCV 2023 • Yang Fu, Shibei Meng, Saihui Hou, Xuecai Hu, Yongzhen Huang
Recent works on pose-based gait recognition have demonstrated the potential of using such simple information to achieve results comparable to silhouette-based methods.
1 code implementation • 6 Mar 2023 • Chao Fan, Saihui Hou, Yongzhen Huang, Shiqi Yu
Gait recognition is a rapidly advancing vision technique for person identification from a distance.
no code implementations • CVPR 2023 • Kang Ma, Ying Fu, Dezhi Zheng, Chunshui Cao, Xuecai Hu, Yongzhen Huang
Specifically, we create a dynamic attention mechanism between the features of neighboring pixels that not only adaptively focuses on key regions but also generates more expressive local motion patterns.
2 code implementations • CVPR 2023 • Weijia Li, Saihui Hou, Chunjie Zhang, Chunshui Cao, Xu Liu, Yongzhen Huang, Yao Zhao
For the cloth-changing problem, video-based ReID is rarely studied due to the lack of a suitable cloth-changing benchmark, and gait recognition is often researched under controlled conditions.
1 code implementation • CVPR 2023 • Chao Fan, Junhao Liang, Chuanfu Shen, Saihui Hou, Yongzhen Huang, Shiqi Yu
To this end, we first develop a flexible and efficient gait recognition codebase named OpenGait.
no code implementations • ICCV 2023 • Kang Ma, Ying Fu, Dezhi Zheng, Yunjie Peng, Chunshui Cao, Yongzhen Huang
Gait recognition has emerged as a promising technique for the long-range retrieval of pedestrians, providing numerous advantages such as accurate identification in challenging conditions and non-intrusiveness, making it highly desirable for improving public safety and security.
1 code implementation • 12 Nov 2022 • Chao Fan, Junhao Liang, Chuanfu Shen, Saihui Hou, Yongzhen Huang, Shiqi Yu
To this end, we first develop a flexible and efficient gait recognition codebase named OpenGait.
no code implementations • 29 Jul 2022 • Yunjie Peng, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang, Zhiqiang He
After that, we summarize and compare the performance of recent occluded person Re-ID methods on four popular datasets: Partial-ReID, Partial-iLIDS, Occluded-ReID, and Occluded-DukeMTMC.
no code implementations • 24 Jul 2022 • Xuqian Ren, Saihui Hou, Chunshui Cao, Xu Liu, Yongzhen Huang
Gait recognition is instrumental in crime prevention and social security, for it can be conducted at a long distance to figure out the identity of persons.
1 code implementation • 28 Jun 2022 • Chao Fan, Saihui Hou, Jilong Wang, Yongzhen Huang, Shiqi Yu
As far as we know, GaitLU-1M is the first large-scale unlabelled gait dataset, and GaitSSB is the first method that achieves remarkable unsupervised results on the aforementioned benchmarks.
1 code implementation • 8 Mar 2022 • Junhao Liang, Chao Fan, Saihui Hou, Chuanfu Shen, Yongzhen Huang, Shiqi Yu
Gait is one of the most promising biometrics to identify individuals at a long distance.
no code implementations • 29 Nov 2021 • Panjian Huang, Xu Liu, Yongzhen Huang
Our results show that PGGAN-SSIM successfully generates 256x256 realistic brain tumor MR images which fill the real image distribution uncovered by the original dataset.
no code implementations • 26 Sep 2020 • Rijun Liao, Weizhi An, Shiqi Yu, Zhu Li, Yongzhen Huang
In this paper, we, therefore, introduce a Dense-View GEIs Set (DV-GEIs) to deal with the challenge of limited view angles.
no code implementations • 29 Sep 2019 • Weiyu Guo, Jiabin Ma, Liang Wang, Yongzhen Huang
As deep neural networks are increasingly used in applications suited for low-power devices, a fundamental dilemma becomes apparent: the trend is to grow models to absorb increasing data that gives rise to memory intensive; however low-power devices are designed with very limited memory that can not store large models.
no code implementations • ICCV 2015 • Chunshui Cao, Xian-Ming Liu, Yi Yang, Yinan Yu, Jiang Wang, Zilei Wang, Yongzhen Huang, Liang Wang, Chang Huang, Wei Xu, Deva Ramanan, Thomas S. Huang
While feedforward deep convolutional neural networks (CNNs) have been a great success in computer vision, it is important to remember that the human visual contex contains generally more feedback connections than foward connections.
no code implementations • CVPR 2015 • Fang Zhao, Yongzhen Huang, Liang Wang, Tieniu Tan
Research efforts have been devoted to learning compact binary codes that preserve semantic similarity based on labels.
no code implementations • 22 Jan 2015 • Wenjuan Gong, Yongzhen Huang, Jordi Gonzalez, and Liang Wang
In this condition, we can combine extracted human blobs with histogram of gradient feature, which is commonly used in mixture of parts model for training body part templates.
no code implementations • NeurIPS 2013 • Fang Zhao, Yongzhen Huang, Liang Wang, Tieniu Tan
Unstructured social group activity recognition in web videos is a challenging task due to 1) the semantic gap between class labels and low-level visual features and 2) the lack of labeled training data.