TaiSu: A 166M Large-scale High-Quality Dataset for Chinese Vision-Language Pre-trainingDownload PDF

Published: 17 Sept 2022, Last Modified: 23 May 2023NeurIPS 2022 Datasets and Benchmarks Readers: Everyone
Keywords: Vision-Language Pretraining, Multi-modality, Dataset
TL;DR: We release a new large-scale dataset for Chinese vision-language pretraining
Abstract: Vision-Language Pre-training (VLP) has been shown to be an efficient method to improve the performance of models on different vision-and-language downstream tasks. Substantial studies have shown that neural networks may be able to learn some general rules about language and visual concepts from a large-scale weakly labeled image-text dataset. However, most of the public cross-modal datasets that contain more than 100M image-text pairs are in English; there is a lack of available large-scale and high-quality Chinese VLP datasets. In this work, we propose a new framework for automatic dataset acquisition and cleaning with which we construct a new large-scale and high-quality cross-modal dataset named as TaiSu, containing 166 million images and 219 million Chinese captions. Compared with the recently released Wukong dataset, our dataset is achieved with much stricter restrictions on the semantic correlation of image-text pairs. We also propose to combine texts collected from the web with texts generated by a pre-trained image-captioning model. To the best of our knowledge, TaiSu is currently the largest publicly accessible Chinese cross-modal dataset. Furthermore, we test our dataset on several vision-language downstream tasks. TaiSu outperforms BriVL by a large margin on the zero-shot image-text retrieval task and zero-shot image classification task. TaiSu also shows better performance than Wukong on the image-retrieval task without using image augmentation for training. Results demonstrate that TaiSu can serve as a promising VLP dataset, both for understanding and generative tasks. More information can be referred to https://github.com/ksOAn6g5/TaiSu.
Author Statement: Yes
URL: https://github.com/ksOAn6g5/TaiSu
Dataset Url: https://github.com/ksOAn6g5/TaiSu
License: This Dataset are provided to You under the terms of the Creative Commons AttributionNonCommercial-ShareAlike 4.0 International Public License (“CC BY-NC-SA 4.0”), with the additional terms included herein. You can access the CC BY-NC-SA 4.0 at https://creativecommons. org/licenses/by-nc-sa/4.0/legalcode. When You download or use the Dataset from the Website or elsewhere, You are agreeing to comply with the terms of CC BY-NC-SA 4.0, and also agreeing to the Dataset Terms. This dataset is only for non-commercial purposes such as academic research, teaching, or scientific publications.
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