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20152023
most citedDualGAN: Unsupervised Dual Learning for Image-to-Image Translation

307 citations · 725 across the 35 of their papers we have counts for

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Showing 2021 · cs.CVShow all

7 papers · 2 filters

cs.CV2021★ 3 cited

Riggable 3D Face Reconstruction via In-Network Optimization

Ziqian Bai, Zhaopeng Cui, Xiaoming Liu +1

This paper presents a method for riggable 3D face reconstruction from monocular images, which jointly estimates a personalized face rig and per-image parameters including expressio…

cs.CV2021★ 3 cited

Stereo Matching by Self-supervision of Multiscopic Vision

Weihao Yuan, Yazhan Zhang, Bingkun Wu +4

Self-supervised learning for depth estimation possesses several advantages over supervised learning. The benefits of no need for ground-truth depth, online fine-tuning, and better…

cs.CV2021★ 3 cited

Learning Camera Localization via Dense Scene Matching

Shitao Tang, Chengzhou Tang, Rui Huang +2

Camera localization aims to estimate 6 DoF camera poses from RGB images. Traditional methods detect and match interest points between a query image and a pre-built 3D model. Recent…

cs.CV2021★ 2 cited

HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences

Feitong Tan, Danhang Tang, Mingsong Dou +9

In this paper, we address the problem of building dense correspondences between human images under arbitrary camera viewpoints and body poses. Prior art either assumes small motion…

cs.CV2021

AR Mapping: Accurate and Efficient Mapping for Augmented Reality

Rui Huang, Chuan Fang, Kejie Qiu +4

Augmented reality (AR) has gained increasingly attention from both research and industry communities. By overlaying digital information and content onto the physical world, AR enab…

cs.CV2021

Learning Efficient Photometric Feature Transform for Multi-view Stereo

Kaizhang Kang, Cihui Xie, Ruisheng Zhu +4

We present a novel framework to learn to convert the perpixel photometric information at each view into spatially distinctive and view-invariant low-level features, which can be pl…

cs.CV2021★ 59 cited

Cluster Contrast for Unsupervised Person Re-Identification

Zuozhuo Dai, Guangyuan Wang, Weihao Yuan +3

State-of-the-art unsupervised re-ID methods train the neural networks using a memory-based non-parametric softmax loss. Instance feature vectors stored in memory are assigned pseud…