Back to Results
First PageMeta Content
Computer vision / Object recognition / Holism / Segmentation / Part-based models / Document Object Model / Imaging / Computing / Vision


Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts Xianjie Chen1 , Roozbeh Mottaghi2 , Xiaobai Liu1 , Sanja Fidler3 , Raquel Urtasun3 , Alan Yuille1 1 University of California, L
Add to Reading List

Open Document

File Size: 4,32 MB

Share Result on Facebook

/

Facility

University of California / University of Toronto / Stanford University / /

IndustryTerm

search space reduction / search space / exhaustive search / approximate solution / /

Organization

University of California / Los Angeles / University of Toronto / Stanford University / /

Person

C. J. Lin / K. W. Chang / PASCAL VOC / X. R. Wang / C. J. Hsieh / A. Vedaldi / V / L. Van Gool / /

Position

use head / head / torso and legs / chains model for detecting parts by their context / Articulated part-based model for joint object detection and pose estimation / model / i.e / low resolution head / /

Product

Remington m24 / /

ProgrammingLanguage

PASCAL / /

ProvinceOrState

California / /

SportsLeague

Stanford University / /

URL

http /

SocialTag