CompCars
Classification
Vehicle
|...
许可协议: Custom

Overview

The Comprehensive Cars (CompCars) dataset contains data from two scenarios, including images from web-nature and surveillance-nature. The web-nature data contains 163 car makes with 1,716 car models. There are a total of 136,726 images capturing the entire cars and 27,618 images capturing the car parts. The full car images are labeled with bounding boxes and viewpoints. Each car model is labeled with five attributes, including maximum speed, displacement, number of doors, number of seats, and type of car. The surveillance-nature data contains 50,000 car images captured in the front view. Please refer to our paper for the details.

Instruction

Use thiss password to unzip: d89551fd190e38

Citation

@InProceedings{Yang_2015_CVPR,
author = {Yang, Linjie and Luo, Ping and Change Loy, Chen and Tang, Xiaoou},
title = {A Large-Scale Car Dataset for Fine-Grained Categorization and Verification},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
(CVPR)},
month = {June},
year = {2015}
}

License

Custom

数据概要
数据格式
Image,
数据量
136.726K
文件大小
17.75GB
发布方
Multimedia Laboratory
The CUHK Multimedia Lab (MMLab) is one of the pioneering institutes on deep learning. In GPU Technology Conference (GTC) 2016, a world-wide technology summit, our lab is recognized as one of the top ten AI pioneers, and listed together with top research groups in the world (e.g. MIT, Stanford, Berkeley, and Univ. of Toronto). Today, we remain one of the most active research labs in computer vision and deep learning, publishing over 40 papers on top conferences (CVPR/ICCV/ECCV/NIPS) every year. Our lab has a large group of talented students, plenty of computational resources, and steady financial support, and free research environment.
数据集反馈
| 313 | 数据量 136.726K | 大小 17.75GB
CompCars
Classification
Vehicle
许可协议: Custom

Overview

The Comprehensive Cars (CompCars) dataset contains data from two scenarios, including images from web-nature and surveillance-nature. The web-nature data contains 163 car makes with 1,716 car models. There are a total of 136,726 images capturing the entire cars and 27,618 images capturing the car parts. The full car images are labeled with bounding boxes and viewpoints. Each car model is labeled with five attributes, including maximum speed, displacement, number of doors, number of seats, and type of car. The surveillance-nature data contains 50,000 car images captured in the front view. Please refer to our paper for the details.

Instruction

Use thiss password to unzip: d89551fd190e38

Citation

@InProceedings{Yang_2015_CVPR,
author = {Yang, Linjie and Luo, Ping and Change Loy, Chen and Tang, Xiaoou},
title = {A Large-Scale Car Dataset for Fine-Grained Categorization and Verification},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
(CVPR)},
month = {June},
year = {2015}
}

License

Custom

数据集反馈
0
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