Unsupervised Depth Completion and Denoising for RGB-D Sensors
Lei Fan,Yunxuan Li,Chen Jiang,Ying Wu,Lei Fan,Yunxuan Li,Chen Jiang,Ying Wu
Depth information is considered valuable as it describes geometric structures, which benefits various robotic tasks. However, the depth acquired by RGB-D sensors still suffers from two deficiencies, i.e., incompletion and noises. Previous methods complete depth by exploring hand-tuned models or raising surface assumptions, while nowadays, deep approaches intend to solve this problem with rendered ...
