Search Results for author: Chengde Wan

Found 9 papers, 3 papers with code

Data-Free Class-Incremental Hand Gesture Recognition

1 code implementation ICCV 2023 Shubhra Aich, Jesus Ruiz-Santaquiteria, Zhenyu Lu, Prachi Garg, K J Joseph, Alvaro Fernandez Garcia, Vineeth N Balasubramanian, Kenrick Kin, Chengde Wan, Necati Cihan Camgoz, Shugao Ma, Fernando de la Torre

Our sampling scheme outperforms SOTA methods significantly on two 3D skeleton gesture datasets, the publicly available SHREC 2017, and EgoGesture3D -- which we extract from a publicly available RGBD dataset.

Class Incremental Learning Hand Gesture Recognition +3

PressureVision: Estimating Hand Pressure from a Single RGB Image

1 code implementation19 Mar 2022 Patrick Grady, Chengcheng Tang, Samarth Brahmbhatt, Christopher D. Twigg, Chengde Wan, James Hays, Charles C. Kemp

We also show that the output of our model depends on the appearance of the hand and cast shadows near contact regions.

Contact mechanics

Dual Grid Net: hand mesh vertex regression from single depth maps

no code implementations ECCV 2020 Chengde Wan, Thomas Probst, Luc van Gool, Angela Yao

In the first stage, the network estimates a dense correspondence field for every pixel on the depth map or image grid to the mesh grid.

regression

Dense 3D Regression for Hand Pose Estimation

1 code implementation CVPR 2018 Chengde Wan, Thomas Probst, Luc van Gool, Angela Yao

Specifically, we decompose the pose parameters into a set of per-pixel estimations, i. e., 2D heat maps, 3D heat maps and unit 3D directional vector fields.

3D Hand Pose Estimation regression

Crossing Nets: Combining GANs and VAEs with a Shared Latent Space for Hand Pose Estimation

no code implementations CVPR 2017 Chengde Wan, Thomas Probst, Luc van Gool, Angela Yao

Regressing the hand pose can then be done by learning a discriminator to estimate the posterior of the latent pose given some depth maps.

3D Hand Pose Estimation

Direction matters: hand pose estimation from local surface normals

no code implementations10 Apr 2016 Chengde Wan, Angela Yao, Luc van Gool

We present a hierarchical regression framework for estimating hand joint positions from single depth images based on local surface normals.

Hand Pose Estimation regression

Towards Predicting the Likeability of Fashion Images

no code implementations17 Nov 2015 Jinghua Wang, Abrar Abdul Nabi, Gang Wang, Chengde Wan, Tian-Tsong Ng

Given attributes as representations, we propose to learn a ranking SPN (sum product networks) to rank pairs of fashion images.

Attribute

Cannot find the paper you are looking for? You can Submit a new open access paper.