no code implementations • 16 Dec 2024 • Yangyang Li, Daqing Liu, Wu Liu, Allen He, Xinchen Liu, Yongdong Zhang, Guoqing Jin
Creative visual concept generation often draws inspiration from specific concepts in a reference image to produce relevant outcomes.
1 code implementation • 16 Nov 2024 • Jinkai Zheng, Xinchen Liu, Boyue Zhang, Chenggang Yan, Jiyong Zhang, Wu Liu, Yongdong Zhang
In particular, the GCM aims to enhance the quality of parsing features by leveraging global features from silhouettes, while the PCM aligns the dynamics of human parts between silhouette and parsing features using the high information entropy in parsing sequences.
no code implementations • 23 Jul 2024 • Xiaodong Chen, Wu Liu, Qian Bao, Xinchen Liu, Quanwei Yang, Ruoli Dai, Tao Mei
With the proposed MINIONS, we conduct experiments on multi-modal motion capture and explore the possibilities of consumer-affordable motion capture using a monocular camera and very few IMUs.
no code implementations • CVPR 2024 • Caoyuan Ma, Yu-Lun Liu, Zhixiang Wang, Wu Liu, Xinchen Liu, Zheng Wang
Our architecture involving both explicit and implicit representation is simple yet effective.
1 code implementation • 29 Nov 2023 • Qi Liu, Xinchen Liu, Kun Liu, Xiaoyan Gu, Wu Liu
Nowadays, the majority of approaches concentrate on the fusion of dense signals (i. e., RGB, optical flow, and depth maps).
1 code implementation • 31 Aug 2023 • Jinkai Zheng, Xinchen Liu, Shuai Wang, Lihao Wang, Chenggang Yan, Wu Liu
Furthermore, due to the lack of suitable datasets, we build the first parsing-based dataset for gait recognition in the wild, named Gait3D-Parsing, by extending the large-scale and challenging Gait3D dataset.
no code implementations • 1 Sep 2022 • Xiaodong Chen, Wu Liu, Xinchen Liu, Yongdong Zhang, Jungong Han, Tao Mei
In DestFormer, the spatial and temporal dimensions of the 4D point cloud videos are decoupled to achieve efficient self-attention for learning both long-term and short-term features.
no code implementations • 1 Sep 2022 • Quanwei Yang, Xinchen Liu, Wu Liu, Hongtao Xie, Xiaoyan Gu, Lingyun Yu, Yongdong Zhang
Human Video Motion Transfer (HVMT) aims to, given an image of a source person, generate his/her video that imitates the motion of the driving person.
1 code implementation • 1 Sep 2022 • Jinkai Zheng, Xinchen Liu, Xiaoyan Gu, Yaoqi Sun, Chuang Gan, Jiyong Zhang, Wu Liu, Chenggang Yan
Current methods that obtain state-of-the-art performance on in-the-lab benchmarks achieve much worse accuracy on the recently proposed in-the-wild datasets because these methods can hardly model the varied temporal dynamics of gait sequences in unconstrained scenes.
no code implementations • 1 Sep 2022 • Guang Yang, Wu Liu, Xinchen Liu, Xiaoyan Gu, Juan Cao, Jintao Li
To close the frequency gap between the natural and synthetic videos, we propose a novel Frequency-based human MOtion TRansfer framework, named FreMOTR, which can effectively mitigate the spatial artifacts and the temporal inconsistency of the synthesized videos.
1 code implementation • CVPR 2022 • Jinkai Zheng, Xinchen Liu, Wu Liu, Lingxiao He, Chenggang Yan, Tao Mei
Based on Gait3D, we comprehensively compare our method with existing gait recognition approaches, which reflects the superior performance of our framework and the potential of 3D representations for gait recognition in the wild.
Ranked #2 on
Gait Recognition
on Gait3D
no code implementations • 9 Mar 2022 • Xiaodong Chen, Xinchen Liu, Wu Liu, Kun Liu, Dong Wu, Yongdong Zhang, Tao Mei
Therefore, researchers start to focus on a new task, Part-level Action Parsing (PAP), which aims to not only predict the video-level action but also recognize the frame-level fine-grained actions or interactions of body parts for each person in the video.
no code implementations • 7 Oct 2021 • Xiaodong Chen, Xinchen Liu, Kun Liu, Wu Liu, Tao Mei
This technical report introduces our 2nd place solution to Kinetics-TPS Track on Part-level Action Parsing in ICCV DeeperAction Workshop 2021.
1 code implementation • ICCV 2021 • Xiaodong Chen, Xinchen Liu, Wu Liu, Xiao-Ping Zhang, Yongdong Zhang, Tao Mei
In this paper, we propose a post-hoc method, named Attribute-guided Metric Distillation (AMD), to explain existing ReID models.
Ranked #26 on
Person Re-Identification
on Market-1501
1 code implementation • 9 Feb 2021 • Jinkai Zheng, Xinchen Liu, Chenggang Yan, Jiyong Zhang, Wu Liu, XiaoPing Zhang, Tao Mei
Despite significant improvement in gait recognition with deep learning, existing studies still neglect a more practical but challenging scenario -- unsupervised cross-domain gait recognition which aims to learn a model on a labeled dataset then adapts it to an unlabeled dataset.
1 code implementation • 8 Dec 2020 • Xinhai Liu, Xinchen Liu, Yu-Shen Liu, Zhizhong Han
The task of point cloud upsampling aims to acquire dense and uniform point sets from sparse and irregular point sets.
3 code implementations • 4 Jun 2020 • Lingxiao He, Xingyu Liao, Wu Liu, Xinchen Liu, Peng Cheng, Tao Mei
General Instance Re-identification is a very important task in the computer vision, which can be widely used in many practical applications, such as person/vehicle re-identification, face recognition, wildlife protection, commodity tracing, and snapshop, etc.. To meet the increasing application demand for general instance re-identification, we present FastReID as a widely used software system in JD AI Research.
Ranked #1 on
Person Re-Identification
on MSMT17-C
no code implementations • CVPR 2019 • Xinchen Liu, Wu Liu, Meng Zhang, Jingwen Chen, Lianli Gao, Chenggang Yan, Tao Mei
On one hand, the actions and storylines in videos provide more important cues for social relation recognition.
no code implementations • 10 Jan 2019 • Xinchen Liu, Wu Liu, Huadong Ma, Shuangqun Li
In this paper, a Progressive Vehicle Search System, named as PVSS, is designed to solve the above problems.
no code implementations • 10 Jan 2019 • Meng Zhang, Xinchen Liu, Wu Liu, Anfu Zhou, Huadong Ma, Tao Mei
To bridge the domain gap, we propose a Multi-Granularity Reasoning framework for social relation recognition from images.
Ranked #3 on
Visual Social Relationship Recognition
on PISC