rabeshi/constrastive-learning-vision-and-language

Vision-and-Language

1. BioGPT ( BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining) Renqian Luo, Liai Sun, Yingce Xia, Tao Qin, Sheng Zhang, Hoifung Poon and Tie-Yan Liu. [[code]] (https://github.com/microsoft/BioGPT)
2. CLIP (Contrastive Language-Image Pre-Training): Learning Transferable Visual Models From Natural Language Supervision Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever arXiv [pdf] [code]
3. Language Models Can See: Plugging Visual Controls in Text Generation Yixuan Su, Tian Lan, Yahui Liu, Fangyu Liu, Dani Yogatama, Yan Wang, Lingpeng Kong, Nigel Collier arXiv [pdf] [code]
4. UMIC: An Unreferenced Metric for Image Captioning via Contrastive Learning Hwanhee Lee, Seunghyun Yoon, Franck Dernoncourt, Trung Bui, Kyomin Jung ACL 2021 [pdf] [code]
5. BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation Junnan Li, Dongxu Li, Caiming Xiong, Steven Hoi arXiv [pdf] [code]
6. CyCLIP: Cyclic Contrastive Language-Image Pretraining Shashank Goel, Hritik Bansal, Sumit Bhatia, Ryan A. Rossi, Vishwa Vinay, Aditya Grover arXiv [pdf] [code]
7. Learning Video Representations using Contrastive Bidirectional Transformer Chen Sun, Fabien Baradel, Kevin Murphy, Cordelia Schmid arXiv [pdf]