175 citations · 434 across the 21 of their papers we have counts for
Showing 2019Show all
2 papers · 1 filter
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.CV2019★ 10 cited
Geometry-Aware Symmetric Domain Adaptation for Monocular Depth Estimation
Shanshan Zhao, Huan Fu, Mingming Gong +1
Supervised depth estimation has achieved high accuracy due to the advanced deep network architectures. Since the groundtruth depth labels are hard to obtain, recent methods try to…