The Comprehensive Cars (CompCars) dataset - 车辆精细识别数据集
The Comprehensive Cars (CompCars) dataset - 车辆精细识别数据集
Multimedia Laboratory - Datasets
http://mmlab.ie.cuhk.edu.hk/datasets.html
The Comprehensive Cars (CompCars) dataset
http://mmlab.ie.cuhk.edu.hk/datasets/comp_cars/index.html
News
Surveillance-nature images are released in the download links as “sv_data.*”. Download all such files, then unzip them with the same password as the web-nature data. We also conducted a fine-grained classification experiment for this part of data. The results are provided in the arXiv paper.
A Large-Scale Car Dataset for Fine-Grained Categorization and Verification
As an extension to our CVPR paper, we conduct experiments for fine-grained car classification, attribute prediction, and car verification with the entire dataset and different deep models. See arXiv paper for the details. Train/test splits can be downloaded here. The fine-tuned GoogLeNet model is uploaded to the Caffe Model Zoo.
A Large-Scale Car Dataset for Fine-Grained Categorization and Verification
http://mmlab.ie.cuhk.edu.hk/datasets/comp_cars/arxiv_data.zip
https://github.com/BVLC/caffe/wiki/Model-Zoo
Description
This dataset is presented in our CVPR 2015 paper,
A Large-Scale Car Dataset for Fine-Grained Categorization and Verification
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.
surveillance [sə'veɪl(ə)ns; -'veɪəns]：n. 监督，监视
displacement [dɪs'pleɪsm(ə)nt]：n. 取代，位移，排水量
The dataset is well prepared for the following computer vision tasks:
- Fine-grained classification
- Attribute prediction
- Car model verification
The train/test subsets of these tasks introduced in our paper are included in the dataset. Researchers are also welcome to utilize it for any other tasks such as image ranking, multi-task learning, and 3D reconstruction.
Note
(1) You need to complete the release agreement form to download the dataset. Please see below.
(2) The CompCars database is available for non-commercial research purposes only.
(3) All images of the CompCars database are obtained from the Internet which are not property of MMLAB, The Chinese University of Hong Kong. The MMLAB is not responsible for the content nor the meaning of these images.
(4) You agree not to reproduce, duplicate, copy, sell, trade, resell or exploit for any commercial purposes, any portion of the images and any portion of derived data.
(5) You agree not to further copy, publish or distribute any portion of the CompCars database. Except, for internal use at a single site within the same organization it is allowed to make copies of the database.
(6) The MMLAB reserves the right to terminate your access to the database at any time.
(7) All submitted papers or any publicly available text using the CompCars database must cite the following paper: A Large-Scale Car Dataset for Fine-Grained Categorization and Verification.
The Chinese University of Hong Kong，CUHK：香港中文大学，港中大
derive [dɪ'raɪv]：vt. 源于，得自，获得 vi. 起源
Hong Kong：香港
Download instructions
Download the CompCars dataset Release Agreement, read it carefully, and complete it appropriately. Note that the agreement should be signed by a full-time staff member (that is, student is not acceptable). Then, please scan the signed agreement and send it to Mr. Linjie Yang (yljatthu(at)gmail.com) and cc to Chen Change Loy (ccloy(at)ie.cuhk.edu.hk). We will verify your request and contact you on how to download the database.
http://mmlab.ie.cuhk.edu.hk/datasets/comp_cars/agreement.pdf
full-time staff：专职人员
Printed Name: Yongqiang Cheng
Signature: Yongqiang Cheng
Date: December 19, 2018
Organization: Deep North, Inc.
Position: Computer Vision Algorithm Engineer
Mailing Address: Suite #3201, Building C, Wangzuoqujiang, Cross Yanxiang Road and South 3rd Ring, Xian, Shaanxi, PRC 710061
Email: [email protected]
Tel: 156****1959
Fax: None
Related datasets
Cars Dataset
http://ai.stanford.edu/~jkrause/cars/car_dataset.html
Caltech-UCSD
https://sites.google.com/visipedia.org/index/datasets
Labeled Faces in the Wild Home
http://vis-www.cs.umass.edu/lfw/
Computational Vision at CALTECH - Data Sets
http://www.vision.caltech.edu/archive.html
References
Printed Name：打印的姓名，工整书写，正楷签名，正体签名，印刷体姓名，用易辨认的字体书写。
Signature：手写体签名。
This is a common misunderstanding in China. In American English, “to print your name” means to write it in printed style letters. The opposite is cursive (where the letters are all joined together, like in your formal signature). It is fine to write you name by hand, just use printed style letters. You do not need to use a printer.