no code implementations • 23 Jul 2023 • Shanlin Sun, Thanh-Tung Le, Chenyu You, Hao Tang, Kun Han, Haoyu Ma, Deying Kong, Xiangyi Yan, Xiaohui Xie
We present Hybrid-CSR, a geometric deep-learning model that combines explicit and implicit shape representations for cortical surface reconstruction.
1 code implementation • 22 Sep 2022 • Deying Kong, Linguang Zhang, Liangjian Chen, Haoyu Ma, Xiangyi Yan, Shanlin Sun, Xingwei Liu, Kun Han, Xiaohui Xie
In this paper, we propose an identity-aware hand mesh estimation model, which can incorporate the identity information represented by the intrinsic shape parameters of the subject.
1 code implementation • 16 Sep 2022 • Haoyu Ma, Zhe Wang, Yifei Chen, Deying Kong, Liangjian Chen, Xingwei Liu, Xiangyi Yan, Hao Tang, Xiaohui Xie
In this paper, we propose the token-Pruned Pose Transformer (PPT) for 2D human pose estimation, which can locate a rough human mask and performs self-attention only within selected tokens.
Ranked #17 on 3D Human Pose Estimation on Human3.6M (using extra training data)
no code implementations • 7 Jun 2022 • Shanlin Sun, Kun Han, Hao Tang, Deying Kong, Junayed Naushad, Xiangyi Yan, Xiaohui Xie
Traditional methods for image registration are primarily optimization-driven, finding the optimal deformations that maximize the similarity between two images.
1 code implementation • CVPR 2022 • Shanlin Sun, Kun Han, Deying Kong, Hao Tang, Xiangyi Yan, Xiaohui Xie
Recently DIFs-based methods have been proposed to handle shape reconstruction and dense point correspondences simultaneously, capturing semantic relationships across shapes of the same class by learning a DIFs-modeled shape template.
no code implementations • 25 Feb 2022 • Kun Han, Shanlin Sun, Xiangyi Yan, Chenyu You, Hao Tang, Junayed Naushad, Haoyu Ma, Deying Kong, Xiaohui Xie
Here we propose a new optimization-based method named DNVF (Diffeomorphic Image Registration with Neural Velocity Field) which utilizes deep neural network to model the space of admissible transformations.
no code implementations • 20 Oct 2021 • Xiangyi Yan, Hao Tang, Shanlin Sun, Haoyu Ma, Deying Kong, Xiaohui Xie
One has to either downsample the image or use cropped local patches to reduce GPU memory usage, which limits its performance.
1 code implementation • 18 Oct 2021 • Haoyu Ma, Liangjian Chen, Deying Kong, Zhe Wang, Xingwei Liu, Hao Tang, Xiangyi Yan, Yusheng Xie, Shih-Yao Lin, Xiaohui Xie
The 3D position encoding guided by the epipolar field provides an efficient way of encoding correspondences between pixels of different views.
Ranked #20 on 3D Human Pose Estimation on Human3.6M (using extra training data)
no code implementations • 25 Sep 2020 • Deying Kong, Haoyu Ma, Xiaohui Xie
In this paper, we extend GNNs along two directions: a) allowing features at each node to be represented by 2D spatial confidence maps instead of 1D vectors; and b) proposing an efficient operation to integrate information from neighboring nodes through 2D convolutions with different learnable kernels at each edge.
no code implementations • 5 Feb 2020 • Deying Kong, Haoyu Ma, Yifei Chen, Xiaohui Xie
In this paper, we propose a new architecture named Rotation-invariant Mixed Graphical Model Network (R-MGMN) to solve the problem of 2D hand pose estimation from a monocular RGB image.
1 code implementation • 24 Jan 2020 • Yifei Chen, Haoyu Ma, Deying Kong, Xiangyi Yan, Jianbao Wu, Wei Fan, Xiaohui Xie
We propose a novel Nonparametric Structure Regularization Machine (NSRM) for 2D hand pose estimation, adopting a cascade multi-task architecture to learn hand structure and keypoint representations jointly.
1 code implementation • 18 Sep 2019 • Deying Kong, Yifei Chen, Haoyu Ma, Xiangyi Yan, Xiaohui Xie
In this paper, we propose a new architecture called Adaptive Graphical Model Network (AGMN) to tackle the task of 2D hand pose estimation from a monocular RGB image.