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ICCV
2001
IEEE
16 years 9 months ago
Feature Selection from Huge Feature Sets
The number of features that can be computed over an image is, for practical purposes, limitless. Unfortunately, the number of features that can be computed and exploited by most c...
José Bins, Bruce A. Draper
ECCV
2008
Springer
16 years 9 months ago
A Segmentation Based Variational Model for Accurate Optical Flow Estimation
Segmentation has gained in popularity in stereo matching. However, it is not trivial to incorporate it in optical flow estimation due to the possible non-rigid motion problem. In t...
Li Xu, Jianing Chen, Jiaya Jia
ECCV
2008
Springer
16 years 9 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...
ECCV
2008
Springer
16 years 9 months ago
Understanding Camera Trade-Offs through a Bayesian Analysis of Light Field Projections
Computer vision has traditionally focused on extracting structure, such as depth, from images acquired using thin-lens or pinhole optics. The development of computational imaging i...
Anat Levin, William T. Freeman, Frédo Duran...
ECCV
2006
Springer
16 years 9 months ago
Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...
Daniel Cremers, Leo Grady