6 papers · 1 filter
Resolution Correspondence Networks
Georgi Tinchev, Shuda Li, Kai Han +2
In this paper, we aim at establishing accurate dense correspondences between a pair of images with overlapping field of view under challenging illumination variation, viewpoint cha…
Dual-Resolution Correspondence Networks
Xinghui Li, Kai Han, Shuda Li +1
We tackle the problem of establishing dense pixel-wise correspondences between a pair of images. In this work, we introduce Dual-Resolution Correspondence Networks (DualRC-Net), to…
Correspondence Networks with Adaptive Neighbourhood Consensus
Shuda Li, Kai Han, Theo W. Costain +2
In this paper, we tackle the task of establishing dense visual correspondences between images containing objects of the same category. This is a challenging task due to large intra…
FlowNet3D++: Geometric Losses For Deep Scene Flow Estimation
Zirui Wang, Shuda Li, Henry Howard-Jenkins +2
We present FlowNet3D++, a deep scene flow estimation network. Inspired by classical methods, FlowNet3D++ incorporates geometric constraints in the form of point-to-plane distance a…
Thinking Outside the Box: Generation of Unconstrained 3D Room Layouts
Henry Howard-Jenkins, Shuda Li, Victor Prisacariu
We propose a method for room layout estimation that does not rely on the typical box approximation or Manhattan world assumption. Instead, we reformulate the geometry inference pro…
HDRFusion: HDR SLAM using a low-cost auto-exposure RGB-D sensor
Shuda Li, Ankur Handa, Yang Zhang +1
We describe a new method for comparing frame appearance in a frame-to-model 3-D mapping and tracking system using an low dynamic range (LDR) RGB-D camera which is robust to brightn…