Video Depth Estimation by Fusing Flow-to-Depth Proposals
Jiaxin Xie,Chenyang Lei,Zhuwen Li,Li Erran Li,Qifeng Chen,Jiaxin Xie,Chenyang Lei,Zhuwen Li,Li Erran Li,Qifeng Chen
Depth from a monocular video can enable billions of devices and robots with a single camera to see the world in 3D. In this paper, we present a model for video depth estimation, which consists of a flow-to-depth layer, a camera pose refinement module, and a depth fusion network. Given optical flow and camera poses, our flow-to-depth layer generates depth proposals and their corresponding confidenc...
