Learning Depth from Stereo
By Fabian H Sinz, Joaquin Quiñonero Candela, Gökhan H. Bakir, Carl E. Rasmussen, Matthias O. Franz. 2004
59 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Geology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Chunhua Shen
- Andrew Zisserman
- Xiaogang Wang
- Andrea Vedaldi
- Dacheng Tao
- Jitendra Malik
- Ming-Hsuan Yang
In Geology
- Nassir Navab
- Federico Tombari
- Vasileios Belagiannis
- David Eigen
- Rob Fergus
- Iro Laina
- Christian Rupprecht
- Luigi Di Stefano
Citations in the corpus
- Depth Map Prediction from a Single Image using a Multi-Scale Deep Network (2014, background): “Machine learning techniques have also been applied in the stereo case, often obtaining better results while relaxing the need for careful camera alignment [8, 13, 21, 19].”
- Deeper Depth Prediction with Fully Convolutional Residual Networks (2016, methodology): “Depth estimation from image data has originally relied on stereo vision [22, 32], using image pairs of the same scene to reconstruct 3D shapes.”