activity
20202022
most citedHigh-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal Fusion

65 citations · 92 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2022

Context Attention Network for Skeleton Extraction

Zixuan Huang, Yunfeng Wang, Zhiwen Chen +3

Skeleton extraction is a task focused on providing a simple representation of an object by extracting the skeleton from the given binary or RGB image. In recent years many attracti…

cs.CV2022★ 2 cited

MVP-Human Dataset for 3D Human Avatar Reconstruction from Unconstrained Frames

Xiangyu Zhu, Tingting Liao, Jiangjing Lyu +6

In this paper, we consider a novel problem of reconstructing a 3D human avatar from multiple unconstrained frames, independent of assumptions on camera calibration, capture space,…

cs.CV2021★ 1 cited

Simple Baseline for Single Human Motion Forecasting

Chenxi Wang, Yunfeng Wang, Zixuan Huang +1

Global human motion forecasting is important in many fields, which is the combination of global human trajectory prediction and local human pose prediction. Visual and social infor…

cs.CV2021★ 65 cited

High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal Fusion

Zhiwei Zhong, Xianming Liu, Junjun Jiang +3

Depth map records distance between the viewpoint and objects in the scene, which plays a critical role in many real-world applications. However, depth map captured by consumer-grad…

cs.CV2020★ 24 cited

Adaptive Linear Span Network for Object Skeleton Detection

Chang Liu, Yunjie Tian, Jianbin Jiao +1

Conventional networks for object skeleton detection are usually hand-crafted. Although effective, they require intensive priori knowledge to configure representative features for o…