216 citations · 352 across the 11 of their papers we have counts for
11 papers
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…
DuNet: Learning Depth Estimation from Dual-Cameras and Dual-Pixels
Yinda Zhang, Neal Wadhwa, Sergio Orts-Escolano +3
Computational stereo has reached a high level of accuracy, but degrades in the presence of occlusions, repeated textures, and correspondence errors along edges. We present a novel…
Discrete Optimization of Ray Potentials for Semantic 3D Reconstruction
Nikolay Savinov, Lubor Ladicky, Christian Haene +1
Dense semantic 3D reconstruction is typically formulated as a discrete or continuous problem over label assignments in a voxel grid, combining semantic and depth likelihoods in a M…
Learning Independent Object Motion from Unlabelled Stereoscopic Videos
Zhe Cao, Abhishek Kar, Christian Haene +1
We present a system for learning motion of independently moving objects from stereo videos. The only human annotation used in our system are 2D object bounding boxes which introduc…
Cost-Sensitive Active Learning for Intracranial Hemorrhage Detection
Weicheng Kuo, Christian Häne, Esther Yuh +2
Deep learning for clinical applications is subject to stringent performance requirements, which raises a need for large labeled datasets. However, the enormous cost of labeling med…
PatchFCN for Intracranial Hemorrhage Detection
Weicheng Kuo, Christian Häne, Esther Yuh +2
This paper studies the problem of detecting and segmenting acute intracranial hemorrhage on head computed tomography (CT) scans. We propose to solve both tasks as a semantic segmen…
Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55
Li Yi, Lin Shao, Manolis Savva +47
We introduce a large-scale 3D shape understanding benchmark using data and annotation from ShapeNet 3D object database. The benchmark consists of two tasks: part-level segmentation…
3D Visual Perception for Self-Driving Cars using a Multi-Camera System: Calibration, Mapping, Localization, and Obstacle Detection
Christian Häne, Lionel Heng, Gim Hee Lee +4
Cameras are a crucial exteroceptive sensor for self-driving cars as they are low-cost and small, provide appearance information about the environment, and work in various weather c…
Learning a Multi-View Stereo Machine
Abhishek Kar, Christian Häne, Jitendra Malik
We present a learnt system for multi-view stereopsis. In contrast to recent learning based methods for 3D reconstruction, we leverage the underlying 3D geometry of the problem thro…
Hierarchical Surface Prediction for 3D Object Reconstruction
Christian Häne, Shubham Tulsiani, Jitendra Malik
Recently, Convolutional Neural Networks have shown promising results for 3D geometry prediction. They can make predictions from very little input data such as a single color image.…
Learning the Matching Function
Ľubor Ladický, Christian Häne, Marc Pollefeys
The matching function for the problem of stereo reconstruction or optical flow has been traditionally designed as a function of the distance between the features describing matched…