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ICCV
2011
IEEE
12 years 7 months ago
Annotator Rationales for Visual Recognition
Traditional supervised visual learning simply asks annotators “what” label an image should have. We propose an approach for image classification problems requiring subjective...
Jeff Donahue, Kristen Grauman
ICRA
2010
IEEE
164views Robotics» more  ICRA 2010»
13 years 6 months ago
Boundary detection based on supervised learning
— Detecting the boundaries of objects is a key step in separating foreground objects from the background, which is useful for robotics and computer vision applications, such as o...
Kiho Kwak, Daniel F. Huber, Jeongsook Chae, Takeo ...
23
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ICCV
2007
IEEE
14 years 9 months ago
Learning to Find Object Boundaries Using Motion Cues
While great strides have been made in detecting and localizing specific objects in natural images, the bottom-up segmentation of unknown, generic objects remains a difficult chall...
Andrew N. Stein, Derek Hoiem, Martial Hebert
ICCV
2007
IEEE
14 years 9 months ago
Recovering Occlusion Boundaries from a Single Image
Occlusion reasoning, necessary for tasks such as navigation and object search, is an important aspect of everyday life and a fundamental problem in computer vision. We believe tha...
Derek Hoiem, Andrew N. Stein, Alexei A. Efros, Mar...
BMVC
2002
13 years 10 months ago
A Qualitative, Multi-scale Grammar For Image Description and Analysis
A qualitative image description grammar with automatic image fitting and object modelling algorithms is presented. The grammar is based on assigning a square sub-region of an imag...
Derek R. Magee