activity
20192023
most citedPoNA: Pose-guided Non-local Attention for Human Pose Transfer

61 citations · 130 across the 12 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

cs.CV2020★ 61 cited

PoNA: Pose-guided Non-local Attention for Human Pose Transfer

Kun Li, Jinsong Zhang, Yebin Liu +2

Human pose transfer, which aims at transferring the appearance of a given person to a target pose, is very challenging and important in many applications. Previous work ignores the…

cs.CV2020

Human Pose Transfer by Adaptive Hierarchical Deformation

Jinsong Zhang, Xingzi Liu, Kun Li

Human pose transfer, as a misaligned image generation task, is very challenging. Existing methods cannot effectively utilize the input information, which often fail to preserve the…

cs.CV2020★ 1 cited

Cross-MPI: Cross-scale Stereo for Image Super-Resolution using Multiplane Images

Yuemei Zhou, Gaochang Wu, Ying Fu +2

Various combinations of cameras enrich computational photography, among which reference-based superresolution (RefSR) plays a critical role in multiscale imaging systems. However,…

cs.GR2020★ 1 cited

Geometry-guided Dense Perspective Network for Speech-Driven Facial Animation

Jingying Liu, Binyuan Hui, Kun Li +5

Realistic speech-driven 3D facial animation is a challenging problem due to the complex relationship between speech and face. In this paper, we propose a deep architecture, called…

cs.CV2020★ 1 cited

Adaptive 3D Face Reconstruction from a Single Image

Kun Li, Jing Yang, Nianhong Jiao +2

3D face reconstruction from a single image is a challenging problem, especially under partial occlusions and extreme poses. This is because the uncertainty of the estimated 2D land…

cs.CV2020★ 6 cited

4D Association Graph for Realtime Multi-person Motion Capture Using Multiple Video Cameras

Yuxiang Zhang, Liang An, Tao Yu +3

This paper contributes a novel realtime multi-person motion capture algorithm using multiview video inputs. Due to the heavy occlusions in each view, joint optimization on the mult…