9 citations · 11 across the 4 of their papers we have counts for
4 papers · 1 filter
CHOSEN: Contrastive Hypothesis Selection for Multi-View Depth Refinement
Di Qiu, Yinda Zhang, Thabo Beeler +5
We propose CHOSEN, a simple yet flexible, robust and effective multi-view depth refinement framework. It can be employed in any existing multi-view stereo pipeline, with straightfo…
NeuralBF: Neural Bilateral Filtering for Top-down Instance Segmentation on Point Clouds
Weiwei Sun, Daniel Rebain, Renjie Liao +4
We introduce a method for instance proposal generation for 3D point clouds. Existing techniques typically directly regress proposals in a single feed-forward step, leading to inacc…
HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching
Vladimir Tankovich, Christian Häne, Yinda Zhang +3
This paper presents HITNet, a novel neural network architecture for real-time stereo matching. Contrary to many recent neural network approaches that operate on a full cost volume…
ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems
Yinda Zhang, Sameh Khamis, Christoph Rhemann +7
In this paper we present ActiveStereoNet, the first deep learning solution for active stereo systems. Due to the lack of ground truth, our method is fully self-supervised, yet it p…