351 citations · 1.2k across the 48 of their papers we have counts for
Showing cs.CVShow all
3 papers · 1 filter
cs.CV2020★ 124 cited
Learning Disentangled Semantic Representation for Domain Adaptation
Ruichu Cai, Zijian Li, Pengfei Wei +3
Domain adaptation is an important but challenging task. Most of the existing domain adaptation methods struggle to extract the domain-invariant representation on the feature space…
cs.CV2019★ 5 cited
Learning Depth from Monocular Videos Using Synthetic Data: A Temporally-Consistent Domain Adaptation Approach
Yipeng Mou, Mingming Gong, Huan Fu +3
Majority of state-of-the-art monocular depth estimation methods are supervised learning approaches. The success of such approaches heavily depends on the high-quality depth labels…
cs.CV2018★ 18 cited
Geometry-Consistent Generative Adversarial Networks for One-Sided Unsupervised Domain Mapping
Huan Fu, Mingming Gong, Chaohui Wang +3
Unsupervised domain mapping aims to learn a function to translate domain X to Y by a function GXY in the absence of paired examples. Finding the optimal GXY without paired data is…