activity
20192024
most citedHuman Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation

13 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2024

Attention-Aware Laparoscopic Image Desmoking Network with Lightness Embedding and Hybrid Guided Embedding

Ziteng Liu, Jiahua Zhu, Bainan Liu +3

This paper presents a novel method of smoke removal from the laparoscopic images. Due to the heterogeneous nature of surgical smoke, a two-stage network is proposed to estimate the…

cs.CV2020★ 1 cited

Synthetic Training for Monocular Human Mesh Recovery

Yu Sun, Qian Bao, Wu Liu +4

Recovering 3D human mesh from monocular images is a popular topic in computer vision and has a wide range of applications. This paper aims to estimate 3D mesh of multiple body part…

cs.IT2020

Double Circulant Self-dual Codes on Sextic Cyclotomy

Tongjiang Yan, Tao Wang, Wenpeng Gao +1

This paper contributes to construct double circulant self-dual codes by sextic cyclotomy. Generator matrixes of a family of pure double circulant codes and a family of double circu…

cs.IT2019

Double Circulant Self-Dual Codes From Generalized Cyclotomic Classes of Order Two

Wenpeng Gao, Tongjiang Yan

In this paper, constructions of some double circulant self-dual codes by generalized cyclotomic classes of order two are presented. This technique is applied to [72, 36, 12] binary…

cs.CV2019★ 13 cited

Human Mesh Recovery from Monocular Images via a Skeleton-disentangled Representation

Sun Yu, Ye Yun, Liu Wu +3

We describe an end-to-end method for recovering 3D human body mesh from single images and monocular videos. Different from the existing methods try to obtain all the complex 3D pos…