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ICCV
1999
IEEE
15 years 10 months ago
Learning Low-Level Vision
We describe a learning-based method for low-level vision problems--estimating scenes from images. We generate a synthetic world of scenes and their corresponding rendered images, m...
William T. Freeman, Egon C. Pasztor
ECCV
2008
Springer
16 years 8 months ago
Object Detection from Large-Scale 3D Datasets Using Bottom-Up and Top-Down Descriptors
We propose an approach for detecting objects in large-scale range datasets that combines bottom-up and top-down processes. In the bottom-up stage, fast-to-compute local descriptors...
Alexander Patterson, Philippos Mordohai, Kostas Da...
PAMI
2012
13 years 8 months ago
Holistic Context Models for Visual Recognition
— A novel framework to context modeling, based on the probability of co-occurrence of objects and scenes is proposed. The modeling is quite simple, and builds upon the availabili...
Nikhil Rasiwasia, Nuno Vasconcelos
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
15 years 8 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang
RT
2001
Springer
15 years 10 months ago
Interactive Sampling and Rendering for Complex and Procedural Geometry
We present a new sampling method for procedural and complex geometries, which allows interactive point-based modeling and rendering of such scenes. For a variety of scenes, object-...
Marc Stamminger, George Drettakis