Abstract A number of techniques for generating mid-level features, including two variants of Soft Assignment, Locality-constrained Linear Coding, and Sparse Coding, are evaluated in the main documen
Visual Category Recognition aims at fast classification of objects, as well as scenery, action, and ...
In object recognition, soft-assignment coding enjoys computational efficiency and conceptual simplic...
In object recognition, soft-assignment coding enjoys computational efficiency and conceptual simplic...
Bag-of-Words lies at a heart of modern object category recognition systems. After descriptors are ex...
In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors from image...
In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors from image...
Many successful models for scene or object recognition transform low-level descriptors (such as Gabo...
Abstract—In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors f...
In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors from image...
The optimal coding hypothesis proposes that the human visual system has adapted to the statistical p...
Discovering visual knowledge from weakly labeled data is crucial to scale up computer vision recogni...
A video captures a sequence and interactions of concepts that can be static, for instance, objects o...
A video captures a sequence and interactions of concepts that can be static, for instance, objects o...
A video captures a sequence and interactions of concepts that can be static, for instance, objects o...
In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors from image...
Visual Category Recognition aims at fast classification of objects, as well as scenery, action, and ...
In object recognition, soft-assignment coding enjoys computational efficiency and conceptual simplic...
In object recognition, soft-assignment coding enjoys computational efficiency and conceptual simplic...
Bag-of-Words lies at a heart of modern object category recognition systems. After descriptors are ex...
In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors from image...
In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors from image...
Many successful models for scene or object recognition transform low-level descriptors (such as Gabo...
Abstract—In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors f...
In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors from image...
The optimal coding hypothesis proposes that the human visual system has adapted to the statistical p...
Discovering visual knowledge from weakly labeled data is crucial to scale up computer vision recogni...
A video captures a sequence and interactions of concepts that can be static, for instance, objects o...
A video captures a sequence and interactions of concepts that can be static, for instance, objects o...
A video captures a sequence and interactions of concepts that can be static, for instance, objects o...
In object recognition, the Bag-of-Words model assumes: i) extraction of local descriptors from image...
Visual Category Recognition aims at fast classification of objects, as well as scenery, action, and ...
In object recognition, soft-assignment coding enjoys computational efficiency and conceptual simplic...
In object recognition, soft-assignment coding enjoys computational efficiency and conceptual simplic...