Oscar and VinVL

Overview

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

VinVL: Revisiting Visual Representations in Vision-Language Models

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.
03/08/2021: Oscar+ pretraining code released, please check the last section in VinVL_MODEL_ZOO.md. All image features and model checkpoints in VinVL are also released. Please check VinVL for details.
04/13/2021: Our Scene Graph Benchmark Repo has been released. Welcome to use the code there to extract image features with VinVL pretrained models.

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 GQA
Metric [email protected] [email protected] [email protected] [email protected] [email protected] M C S C S test-std test-P test-std
SoTA_S 39.2 68.0 56.6 84.5 38.9 29.2 129.8 22.4 61.5 9.2 70.92 58.80 63.17
SoTA_B 54.0 80.8 70.0 91.1 40.5 29.7 137.6 22.8 86.58 12.38 73.67 79.30 -
SoTA_L 57.5 82.8 73.5 92.2 41.7 30.6 140.0 24.5 - - 74.93 81.47 -
----- --- --- --- --- --- --- --- --- --- --- --- --- ---
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 61.62
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 -
----- --- --- --- --- --- --- --- --- --- --- --- --- ---
VinVL_B 58.1 83.2 74.6 92.6 40.9 30.9 140.6 25.1 92.46 13.07 76.12 83.08 64.65
VinVL_L 58.8 83.5 75.4 92.9 41.0 31.1 140.9 25.2 - - 76.62 83.98 -
gain 1.3 0.7 1.9 0.6 -0.7 0.5 0.9 0.7 5.9 0.7 1.69 2.51 1.48

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

Download

We released pre-trained models, datasets, VinVL image features, and Oscar+ pretraining corpus for downstream tasks. Please check VinVL_DOWNLOAD.md for details.

To download checkpoints for the Vanilla OSCAR, please check DOWNLOAD.md for details.

Installation

Check INSTALL.md for installation instructions.

Model Zoo

Check MODEL_ZOO.md for scripts to run oscar downstream finetuning.

Check VinVL_MODEL_ZOO.md for scripts to run oscar+ pretraining and downstream finetuning.

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={ECCV 2020},
  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={CVPR 2021},
  year={2021}
}

License

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

Owner
Microsoft
Open source projects and samples from Microsoft
Microsoft
CVPR 2020 oral paper: Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax.

Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax ⚠️ Latest: Current repo is a complete version. But we delet

FishYuLi 341 Dec 23, 2022
Implementation of Squeezenet in pytorch, pretrained models on Cifar 10 data to come

Pytorch Squeeznet Pytorch implementation of Squeezenet model as described in https://arxiv.org/abs/1602.07360 on cifar-10 Data. The definition of Sque

gaurav pathak 86 Oct 28, 2022
Metadata-Extractor - Metadata Extractor Script can be used to read in exif metadata

Metadata Extractor The exifextract script can be used to read in exif metadata f

1 Feb 16, 2022
TensorFlow Implementation of Unsupervised Cross-Domain Image Generation

Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle

Yunjey Choi 865 Nov 17, 2022
Solving Zero-Shot Learning in Named Entity Recognition with Common Sense Knowledge

Zero-Shot Learning in Named Entity Recognition with Common Sense Knowledge Associated code for the paper Zero-Shot Learning in Named Entity Recognitio

Søren Hougaard Mulvad 13 Dec 25, 2022
[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

Anycost GAN video | paper | website Anycost GANs for Interactive Image Synthesis and Editing Ji Lin, Richard Zhang, Frieder Ganz, Song Han, Jun-Yan Zh

MIT HAN Lab 726 Dec 28, 2022
Pytorch implementation of "Training a 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet"

Token Labeling: Training an 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (arxiv) This is a Pytorch implementation of our te

蒋子航 383 Dec 27, 2022
Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning

Conservative and Adaptive Penalty for Model-Based Safe Reinforcement Learning This is the official repository for Conservative and Adaptive Penalty fo

7 Nov 22, 2022
Yolov5 deepsort inference,使用YOLOv5+Deepsort实现车辆行人追踪和计数,代码封装成一个Detector类,更容易嵌入到自己的项目中

使用YOLOv5+Deepsort实现车辆行人追踪和计数,代码封装成一个Detector类,更容易嵌入到自己的项目中。

813 Dec 31, 2022
Adaptable tools to make reinforcement learning and evolutionary computation algorithms.

Pearl The Parallel Evolutionary and Reinforcement Learning Library (Pearl) is a pytorch based package with the goal of being excellent for rapid proto

38 Jan 01, 2023
Rule Based Classification Project For Python

Rule-Based-Classification-Project (ENG) Business Problem: A game company wants to create new level-based customer definitions (personas) by using some

Deniz Can OĞUZ 4 Oct 29, 2022
Unsupervised Pre-training for Person Re-identification (LUPerson)

LUPerson Unsupervised Pre-training for Person Re-identification (LUPerson). The repository is for our CVPR2021 paper Unsupervised Pre-training for Per

143 Dec 24, 2022
Multi-Stage Episodic Control for Strategic Exploration in Text Games

XTX: eXploit - Then - eXplore Requirements First clone this repo using git clone https://github.com/princeton-nlp/XTX.git Please create two conda envi

Princeton Natural Language Processing 9 May 24, 2022
Caffe-like explicit model constructor. C(onfig)Model

cmodel Caffe-like explicit model constructor. C(onfig)Model Installation pip install git+https://github.com/bonlime/cmodel Usage In order to allow usi

1 Feb 18, 2022
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors

CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors   In order to facilitate the res

yujmo 11 Dec 12, 2022
The fundamental package for scientific computing with Python.

NumPy is the fundamental package needed for scientific computing with Python. Website: https://www.numpy.org Documentation: https://numpy.org/doc Mail

NumPy 22.4k Jan 09, 2023
A PyTorch implementation of the paper Mixup: Beyond Empirical Risk Minimization in PyTorch

Mixup: Beyond Empirical Risk Minimization in PyTorch This is an unofficial PyTorch implementation of mixup: Beyond Empirical Risk Minimization. The co

Harry Yang 121 Dec 17, 2022
Regularizing Generative Adversarial Networks under Limited Data (CVPR 2021)

Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r

Google 148 Nov 18, 2022
A gesture recognition system powered by OpenPose, k-nearest neighbours, and local outlier factor.

OpenHands OpenHands is a gesture recognition system powered by OpenPose, k-nearest neighbours, and local outlier factor. Currently the system can iden

Paul Treanor 12 Jan 10, 2022
PyJokes - Joking around with Python library pyjokes

Hi, it's Muhaimin again 👋 This is something unorthodox but cool. Don't forget t

Muhaimin A. Salay Kanton 1 Feb 02, 2022