Addition of VisualBERT
# 🌟 New model addition
## Model description
The VisualBERT model is used for multi-modal processing when the modes of images and text are present. It takes in object detection features from images, and combines them with textual embeddings from the pre-trained BERT models, pre-trained the whole thing on COCO image captioning data, using a similar MLM task as BERT. It has been shown to work well on several multi-modal tasks such as VQA, VCR, NLVR, etc.

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## Open source status

The source code presented along with the paper can be found at 
https://github.com/uclanlp/visualbert
* [x] the model implementation is available: (give details)
The model implementation can be found on the GitHub repository, in the models section: https://github.com/uclanlp/visualbert/tree/master/models
This code was provided along with the paper.
Another implementation, which is slightly harder to understand because of complex dependencies, is implemented in the Facebook Research's MMF framework: https://github.com/facebookresearch/mmf/blob/master/mmf/models/visual_bert.py

* [x] the model weights are available: (give details)
The model checkpoints that the authors used are presented as drive links in the given repository, depending on which pre-training we want. There are several links on the README file of the GitHub repository.
* [x] who are the authors: (mention them, if possible by @gh-username)
- Kai-Wei Chang: @KaiWeiChang
- Liunian Harold Li: @liunian-harold-li
- Mark Yatskar
- Da Yin
- Cho-Jui Hsieh
- Kai-Wei Chang

I want to contribute the model myself, please let me know if this is the right avenue for this, and how I can contribute.
This is very interesting!<|||||>This has been proposed before as a separate issue but no action was taken. Hence, I thought I'll start implementing some of the multi-modal models one by one.<|||||>Please let @liunian-harold-li and me know if you need any help. We can also provide the pre-trained models. <|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
