activity
20182023
most citedLight Field Reconstruction Using Convolutional Network on EPI and Extended Applications

165 citations · 355 across the 26 of their papers we have counts for

collaborators
Showing 2020Show all

11 papers · 1 filter

cs.CV202061 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.CV20202 cited

Vehicle Reconstruction and Texture Estimation Using Deep Implicit Semantic Template Mapping

Xiaochen Zhao, Zerong Zheng, Chaonan Ji +5

We introduce VERTEX, an effective solution to recover 3D shape and intrinsic texture of vehicles from uncalibrated monocular input in real-world street environments. To fully utili…

cs.CV20201 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.CV2020

Deep Implicit Templates for 3D Shape Representation

Zerong Zheng, Tao Yu, Qionghai Dai +1

Deep implicit functions (DIFs), as a kind of 3D shape representation, are becoming more and more popular in the 3D vision community due to their compactness and strong representati…

cs.GR20201 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.CV20203 cited

NormalGAN: Learning Detailed 3D Human from a Single RGB-D Image

Lizhen Wang, Xiaochen Zhao, Tao Yu +2

We propose NormalGAN, a fast adversarial learning-based method to reconstruct the complete and detailed 3D human from a single RGB-D image. Given a single front-view RGB-D image, N…