Oscar: Object-Semantics Aligned Pre-training for Vision-and-Language Tasks

Updates

05/28/2020: Released finetuned models on downstream tasks, please check MODEL_ZOO.md.
05/15/2020: Released pretrained models, datasets, and code for downstream tasks finetuning.
01/13/2021: our new work VinVL proposed OSCAR+, an improved version of OSCAR, and provided a better object-attribute detection model to extract features for V+L tasks. The VinVL work achieved SOTA performance on all seven V+L tasks here. Please stay tuned for the model and code release.

Introduction

This repository contains source code necessary to reproduce the results presented in the paper Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks. We propose a new cross-modal pre-training method Oscar (Object-Semantics Aligned Pre-training). It leverages object tags detected in images as anchor points to significantly ease the learning of image-text alignments. We pre-train Oscar on the public corpus of 6.5 million text-image pairs, and fine-tune it on downstream tasks, creating new state-of-the-arts on six well-established vision-language understanding and generation tasks. For more on this project, see the Microsoft Research Blog post.

Performance

Task	t2i	t2i	i2t	i2t	IC	IC	IC	IC	NoCaps	NoCaps	VQA	NLVR2
Metric	R@1	R@5	R@1	R@5	B@4	M	C	S	C	S	test-std	test-P
SoTA_S	39.2	68.0	56.6	84.5	38.9	29.2	129.8	22.4	61.5	9.2	70.90	53.50
SoTA_B	48.4	76.7	63.3	87.0	39.5	29.3	129.3	23.2	73.1	11.2	72.54	78.87
SoTA_L	51.7	78.4	66.6	89.4	-	-	-	-	-	-	73.40	79.50
-----	---	---	---	---	---	---	---	---	---	---	---	---
Oscar_B	54.0	80.8	70.0	91.1	40.5	29.7	137.6	22.8	78.8	11.7	73.44	78.36
Oscar_L	57.5	82.8	73.5	92.2	41.7	30.6	140.0	24.5	80.9	11.3	73.82	80.05
gain	5.8	4.4	6.9	2.8	2.2	1.3	10.7	1.3	7.8	0.5	0.42	0.55

t2i: text-to-image retrieval; i2t: image-to-text retrieval; IC: image captioning on COCO.

Download

We released pre-trained models and datasets for downstream tasks. Please check DOWNLOAD.md for details.

Installation

Check INSTALL.md for installation instructions.

Model Zoo

Check MODEL_ZOO.md for scripts to run each downstream tasks and the expected performance.

Citations

Please consider citing this paper if you use the code:

@article{li2020oscar,
  title={Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks},
  author={Li, Xiujun and Yin, Xi and Li, Chunyuan and Hu, Xiaowei and Zhang, Pengchuan and Zhang, Lei and Wang, Lijuan and Hu, Houdong and Dong, Li and Wei, Furu and Choi, Yejin and Gao, Jianfeng},
  journal={arXiv preprint arXiv:2004.06165},
  year={2020}
}

@article{zhang2021vinvl,
  title={VinVL: Making Visual Representations Matter in Vision-Language Models},
  author={Zhang, Pengchuan and Li, Xiujun and Hu, Xiaowei and Yang, Jianwei and Zhang, Lei and Wang, Lijuan and Choi, Yejin and Gao, Jianfeng},
  journal={arXiv preprint arXiv:2101.00529},
  year={2021}
}

License

Oscar is released under the MIT license. See LICENSE for details.

voxlogic/Oscar