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CVPR
2009
IEEE
15 years 2 months ago
A Multi-View Probabilistic Model for 3D Object Classes
We propose a novel probabilistic framework for learning visual models of 3D object categories by combining appearance information and geometric constraints. Objects are represen...
Fei-Fei Li 0002, Hao Su, Min Sun, Silvio Savarese
ICANN
2010
Springer
13 years 8 months ago
Learning Invariant Visual Shape Representations from Physics
3D shape determines an object's physical properties to a large degree. In this article, we introduce an autonomous learning system for categorizing 3D shape of simulated objec...
Mathias Franzius, Heiko Wersing
ECCV
2000
Springer
14 years 9 months ago
Learning to Recognize 3D Objects with SNoW
This paper describes a novel view-based learning algorithm for 3D object recognition from 2D images using a network of linear units. The SNoW learning architecture is a sparse netw...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
CVPR
2007
IEEE
14 years 9 months ago
3D Probabilistic Feature Point Model for Object Detection and Recognition
This paper presents a novel statistical shape model that can be used to detect and localise feature points of a class of objects in images. The shape model is inspired from the 3D...
Sami Romdhani, Thomas Vetter
CVPR
2010
IEEE
14 years 23 days ago
Learning 3D Action Models from a few 2D videos for View Invariant Action Recognition
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
Pradeep Natarajan, Vivek Singh, Ram Nevatia