no code implementations • 18 Apr 2024 • Wenfeng Zhang, Xin Li, Anqi Li, Xiaoting Huang, Ti Wang, Honglei Gao
Traffic flow prediction is an essential task in constructing smart cities and is a typical Multivariate Time Series (MTS) Problem.
no code implementations • 4 Feb 2024 • Ti Wang, Mengyuan Liu, Hong Liu, Bin Ren, Yingxuan You, Wenhao Li, Nicu Sebe, Xia Li
We observe that previous optimization-based methods commonly rely on projection constraint, which only ensures alignment in 2D space, potentially leading to the overfitting problem.
1 code implementation • ICCV 2023 • Yingxuan You, Hong Liu, Ti Wang, Wenhao Li, Runwei Ding, Xia Li
Despite significant progress in single image-based 3D human mesh recovery, accurately and smoothly recovering 3D human motion from a video remains challenging.
1 code implementation • 27 Apr 2023 • Ti Wang, Hong Liu, Runwei Ding, Wenhao Li, Yingxuan You, Xia Li
Despite substantial progress in 3D human pose estimation from a single-view image, prior works rarely explore global and local correlations, leading to insufficient learning of human skeleton representations.
1 code implementation • 10 Mar 2023 • Yingxuan You, Hong Liu, Xia Li, Wenhao Li, Ti Wang, Runwei Ding
3D human mesh recovery from a 2D pose plays an important role in various applications.
Ranked #146 on 3D Human Pose Estimation on Human3.6M
no code implementations • 20 Dec 2013 • Ti Wang, Daniel L. Silver
This paper presents an unsupervised multi-modal learning system that learns associative representation from two input modalities, or channels, such that input on one channel will correctly generate the associated response at the other and vice versa.