no code implementations • ECCV 2020 • Yunpeng Chang, Zhigang Tu, Wei Xie, Junsong Yuan
Because of the ambiguous definition of anomaly and the complexity of real data, anomaly detection in videos is one of the most challenging problems in intelligent video surveillance.
no code implementations • 18 Mar 2024 • Jiaxu Zhang, Xin Chen, Gang Yu, Zhigang Tu
Our key insight is to embed motion style into a cross-modality latent space and perceive the cross-structure skeleton topologies, allowing for motion stylization within a canonical motion space.
no code implementations • 19 Oct 2023 • Jiaxu Zhang, Shaoli Huang, Zhigang Tu, Xin Chen, Xiaohang Zhan, Gang Yu, Ying Shan
In this work, we present TapMo, a Text-driven Animation Pipeline for synthesizing Motion in a broad spectrum of skeleton-free 3D characters.
no code implementations • ICCV 2023 • Zhisheng Huang, Yujin Chen, Di Kang, Jinlu Zhang, Zhigang Tu
We propose PHRIT, a novel approach for parametric hand mesh modeling with an implicit template that combines the advantages of both parametric meshes and implicit representations.
1 code implementation • CVPR 2023 • Jiaxu Zhang, Junwu Weng, Di Kang, Fang Zhao, Shaoli Huang, Xuefei Zhe, Linchao Bao, Ying Shan, Jue Wang, Zhigang Tu
Driven by our explored distance-based losses that explicitly model the motion semantics and geometry, these two modules can learn residual motion modifications on the source motion to generate plausible retargeted motion in a single inference without post-processing.
no code implementations • 7 May 2022 • Zhengbo Zhang, Chunluan Zhou, Zhigang Tu
Knowledge distillation is widely adopted in semantic segmentation to reduce the computation cost. The previous knowledge distillation methods for semantic segmentation focus on pixel-wise feature alignment and intra-class feature variation distillation, neglecting to transfer the knowledge of the inter-class distance in the feature space, which is important for semantic segmentation.
no code implementations • 20 Mar 2022 • Zhigang Tu, Hongyan Li, Wei Xie, Yuanzhong Liu, Shifu Zhang, Baoxin Li, Junsong Yuan
Video super-resolution is currently one of the most active research topics in computer vision as it plays an important role in many visual applications.
1 code implementation • CVPR 2022 • Jinlu Zhang, Zhigang Tu, Jianyu Yang, Yujin Chen, Junsong Yuan
Recent transformer-based solutions have been introduced to estimate 3D human pose from 2D keypoint sequence by considering body joints among all frames globally to learn spatio-temporal correlation.
Ranked #6 on Monocular 3D Human Pose Estimation on Human3.6M
2 code implementations • TIP 2022 • Yuanzhong Liu, Junsong Yuan, Zhigang Tu
Action visual tempo characterizes the dynamics and the temporal scale of an action, which is helpful to distinguish human actions that share high similarities in visual dynamics and appearance.
Ranked #14 on Action Recognition on Something-Something V1
no code implementations • 8 Feb 2022 • Zhigang Tu, Jiaxu Zhang, Hongyan Li, Yujin Chen, Junsong Yuan
In recent years, graph convolutional networks (GCNs) play an increasingly critical role in skeleton-based human action recognition.
no code implementations • 24 Jan 2022 • Zhigang Tu, Zhisheng Huang, Yujin Chen, Di Kang, Linchao Bao, Bisheng Yang, Junsong Yuan
We present a method for reconstructing accurate and consistent 3D hands from a monocular video.
1 code implementation • CVPR 2021 • Yujin Chen, Zhigang Tu, Di Kang, Linchao Bao, Ying Zhang, Xuefei Zhe, Ruizhi Chen, Junsong Yuan
For the first time, we demonstrate the feasibility of training an accurate 3D hand reconstruction network without relying on manual annotations.
1 code implementation • 16 Feb 2021 • Lequan Chen, Wei Xie, Zhigang Tu, Jinglei Guo, Yaping Tao, Xinming Wang
Visual character attributes play a key role in retrieving the query person, which has been explored in Re-ID but has been ignored in Person Search.
no code implementations • ACCV 2020 • Yuanzhong Liu, Zhigang Tu, Liyu Lin, Xing Xie, and Qianqing Qin
In this paper, we exploit better ways to use motion information in a unified end-to-end trainable network architecture.
no code implementations • 28 Jun 2020 • Yujin Chen, Zhigang Tu, Di Kang, Ruizhi Chen, Linchao Bao, Zhengyou Zhang, Junsong Yuan
In this work, we propose to consider hand and object jointly in feature space and explore the reciprocity of the two branches.
no code implementations • 23 Jul 2018 • Kang Dang, Chunluan Zhou, Zhigang Tu, Michael Hoy, Justin Dauwels, Junsong Yuan
One major challenge for this task is that when an actor performs an action, different body parts of the actor provide different types of cues for the action category and may receive inconsistent action labeling when they are labeled independently.
no code implementations • CVPR 2018 • Shizheng Wang, Wenjuan Liao, Phil Surman, Zhigang Tu, Yuanjin Zheng, Junsong Yuan
Multi-layer light field displays are a type of computational three-dimensional (3D) display which has recently gained increasing interest for its holographic-like effect and natural compatibility with 2D displays.