├── LICENSE ├── MM2021Dataset.png └── README.md /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2021 Jonathan Wang 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /MM2021Dataset.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/NjtechCVLab/RSTPReid-Dataset/5dbb31cdc6844dd9c8aad3ac02367facadcd6b50/MM2021Dataset.png -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # RSTPReid-Dataset 2 | RSTPReid Dataset for our ACMMM2021 accepted paper [DSSL: Deep Surroundings-person Separation Learning for Text-based Person Retrieval](https://arxiv.org/abs/2109.05534) [1]. 3 | 4 | ![Dataset](https://github.com/NjtechCVLab/RSTPReid-Dataset/blob/main/MM2021Dataset.png) 5 | 6 | ## Introduction 7 | 8 | To properly handle real scenarios, we construct a new dataset called Real Scenario Text-based Person Re-identification (RSTPReid) based on [MSMT17](https://openaccess.thecvf.com/content_cvpr_2018/papers/Wei_Person_Transfer_GAN_CVPR_2018_paper.pdf) [2]. RSTPReid contains 20505 images of 4,101 persons from 15 cameras. Each person has 5 corresponding images taken by different cameras with complex both indoor and outdoor scene transformations and backgrounds in various periods of time, which makes RSTPReid much more challenging and more adaptable to real scenarios. Each image is annotated with 2 textual descriptions. For data division, **3701 (index < 18505), 200 (18505 <= index < 19505) and 200 (index >= 19505)** identities are utilized for training, validation and testing, respectively **(Marked by item 'split' in the json file)**. Each sentence is no shorter than 23 words. 9 | 10 | Considering that the RSTPReid dataset is newly constructed and is relatively small in data size comparing with CUHK-PEDES, we sepatarely trained each model for 10 times and reported the average results on the validation set in Table 1 to avoid occasional and unstable performance. Moreover, in this paper we only use RSTPReid to make a preliminary analysis of the five proposed alignment paradigms and take the results as a further proof of the validity of each component. Most of the experiments in this paper are still conducted using CHUK-PEDES, where the final results on the testing set are reported. 11 | 12 | On the testing set of RSTPReid, DSSL achieves **39.05%**, **62.60%** and **73.95%** of top-1, top-5 and top-10 accuracies, respectively. More detailed experimental analysis will be conducted on RETPReid along with CUHK-PEDES, which will be reported in the extension of this paper. 13 | 14 | ## Dataset Access 15 | 16 | ### Google Drive 17 | Link: [https://drive.google.com/file/d/1HTeDZUVrZr6nL56ZlkYBNqjSWh3IGV2X/view?usp=sharing](https://drive.google.com/file/d/1HTeDZUVrZr6nL56ZlkYBNqjSWh3IGV2X/view?usp=sharing) 18 | 19 | ### Baidu Netdisk 20 | Link: [https://pan.baidu.com/s/1NkY1dRcvz5rra1mpopyuvQ?pwd=mmkl](https://pan.baidu.com/s/1NkY1dRcvz5rra1mpopyuvQ?pwd=mmkl) 21 | Password: mmkl 22 | 23 | ## Reference 24 | 25 | [1] Zhu A, Wang Z, Li Y, et al. DSSL: Deep Surroundings-person Separation Learning for Text-based Person Retrieval[C]//Proceedings of the 29th ACM International Conference on Multimedia. 2021: 209-217. 26 | 27 | [2] Wei L, Zhang S, Gao W, et al. Person transfer gan to bridge domain gap for person re-identification[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 79-88. 28 | --------------------------------------------------------------------------------