We describe an algorithm for automatically learning discriminative components of objects with SVM classifiers. It is based on growing image parts by minimizing theoretical bounds ...
Bernd Heisele, Thomas Serre, Massimiliano Pontil, ...
This article proposes a method for learning object templates
composed of local sketches and local textures, and
investigates the relative importance of the sketches and textures
...
Haifeng Gong, Song Chun Zhu, Ying Nian Wu, Zhangzh...
Traditional approaches to object detection only look at local pieces of the image, whether it be within a sliding window or the regions around an interest point detector. However, ...
Kevin P. Murphy, Antonio B. Torralba, Daniel Eaton...
Human superiority over computers in identifying natural objects like clouds, water, grass etc. comes from two capabilities: the capability to maintain a growing knowledge base per...
In this paper, an integrated resolution up-conversion and compression artifacts removal algorithm is proposed. Local image patterns are classified into object details or coding ar...