A large-scale car dataset for fine-grained categorization and verification
Refereed conference paper presented and published in conference proceedings


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AbstractThis paper aims to highlight vision related tasks centered around 'car', which has been largely neglected by vision community in comparison to other objects. We show that there are still many interesting car-related problems and applications, which are not yet well explored and researched. To facilitate future car-related research, in this paper we present our on-going effort in collecting a large-scale dataset, 'CompCars', that covers not only different car views, but also their different internal and external parts, and rich attributes. Importantly, the dataset is constructed with a cross-modality nature, containing a surveillance-nature set and a web-nature set. We further demonstrate a few important applications exploiting the dataset, namely car model classification, car model verification, and attribute prediction. We also discuss specific challenges of the car-related problems and other potential applications that worth further investigations. The latest dataset can be downloaded at http://mmlab.ie.cuhk.edu.hk/ datasets/comp-cars/index.html.
All Author(s) ListYang L., Luo P., Loy C.C., Tang X.
Name of ConferenceIEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
Start Date of Conference07/06/2015
End Date of Conference12/06/2015
Place of ConferenceBoston
Country/Region of ConferenceUnited States of America
Detailed descriptionorganized by IEEE Computer Society,
Year2015
Month10
Day14
Volume Number07-12-June-2015
Pages3973 - 3981
ISBN9781467369640
ISSN1063-6919
LanguagesEnglish-United Kingdom

Last updated on 2020-11-09 at 01:12