13 citations · 22 across the 4 of their papers we have counts for
5 papers
DesNet: Decomposed Scale-Consistent Network for Unsupervised Depth Completion
Zhiqiang Yan, Kun Wang, Xiang Li +3
Unsupervised depth completion aims to recover dense depth from the sparse one without using the ground-truth annotation. Although depth measurement obtained from LiDAR is usually s…
Regularizing Nighttime Weirdness: Efficient Self-supervised Monocular Depth Estimation in the Dark
Kun Wang, Zhenyu Zhang, Zhiqiang Yan +4
Monocular depth estimation aims at predicting depth from a single image or video. Recently, self-supervised methods draw much attention since they are free of depth annotations and…
Learning to Aggregate and Personalize 3D Face from In-the-Wild Photo Collection
Zhenyu Zhang, Yanhao Ge, Renwang Chen +6
Non-parametric face modeling aims to reconstruct 3D face only from images without shape assumptions. While plausible facial details are predicted, the models tend to over-depend on…
Online Adaptation through Meta-Learning for Stereo Depth Estimation
Zhenyu Zhang, Stéphane Lathuilière, Andrea Pilzer +3
In this work, we tackle the problem of online adaptation for stereo depth estimation, that consists in continuously adapting a deep network to a target video recordedin an environm…
When Work Matters: Transforming Classical Network Structures to Graph CNN
Wenting Zhao, Chunyan Xu, Zhen Cui +4
Numerous pattern recognition applications can be formed as learning from graph-structured data, including social network, protein-interaction network, the world wide web data, know…