2 citations · 4 across the 3 of their papers we have counts for
4 papers · 1 filter
PLNet: Plane and Line Priors for Unsupervised Indoor Depth Estimation
Hualie Jiang, Laiyan Ding, Junjie Hu +1
Unsupervised learning of depth from indoor monocular videos is challenging as the artificial environment contains many textureless regions. Fortunately, the indoor scenes are full…
Unsupervised Monocular Depth Perception: Focusing on Moving Objects
Hualie Jiang, Laiyan Ding, Zhenglong Sun +1
As a flexible passive 3D sensing means, unsupervised learning of depth from monocular videos is becoming an important research topic. It utilizes the photometric errors between the…
IMENet: Joint 3D Semantic Scene Completion and 2D Semantic Segmentation through Iterative Mutual Enhancement
Jie Li, Laiyan Ding, Rui Huang
3D semantic scene completion and 2D semantic segmentation are two tightly correlated tasks that are both essential for indoor scene understanding, because they predict the same sem…
DiPE: Deeper into Photometric Errors for Unsupervised Learning of Depth and Ego-motion from Monocular Videos
Hualie Jiang, Laiyan Ding, Zhenglong Sun +1
Unsupervised learning of depth and ego-motion from unlabelled monocular videos has recently drawn great attention, which avoids the use of expensive ground truth in the supervised…