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Last update on 2022/08/19. 4 | 5 | ## Table of Contents 6 | 7 | * [Image-based Visual Dialog](#Image-based-Visual-Dialog) 8 | * [Video-based Visual Dialog](#video-based-Visual-Dialog) 9 | * [Other Resources](#other-resources) 10 | 11 | 12 | # Image-based Visual Dialog 13 | 14 | ## Visual Dialog 15 | 16 | 1. [Visual Dialog](https://arxiv.org/abs/1611.08669), CVPR 2017, [[code]](https://github.com/batra-mlp-lab/visdial) 17 | 18 | 2. [Best of Both Worlds: Transferring Knowledge from Discriminative Learning to a Generative Visual Dialog Model](https://arxiv.org/abs/1706.01554), NIPS 2017, [[code]](https://github.com/jiasenlu/visDial.pytorch) 19 | 20 | 3. [Are You Talking to Me? Reasoned Visual Dialog Generation through Adversarial Learning](https://arxiv.org/abs/1711.07613), CVPR 2018 21 | 22 | 4. [Image-Question-Answer Synergistic Network for Visual Dialog](https://arxiv.org/abs/1902.09774), CVPR 2019 23 | 24 | 5. [Reasoning Visual Dialogs with Structural and Partial Observations](https://arxiv.org/abs/1904.05548), CVPR, 2019, [[code]](https://github.com/zilongzheng/visdial-gnn) 25 | 26 | 6. [Recursive Visual Attention in Visual Dialog](https://arxiv.org/abs/1812.02664), CVPR 2019, [[code]](https://github.com/yuleiniu/rva) 27 | 28 | 7. [Dual Visual Attention Network for Visual Dialog](), IJCAI 2019 29 | 30 | 8. [Making History Matter: History-Advantage Sequence Training for Visual Dialog](https://arxiv.org/abs/1902.09326), ICCV 2019 31 | 32 | 9. [Granular Multimodal Attention Networks for Visual Dialog](https://arxiv.org/abs/1910.05728), ICCV Workshop 2019 33 | 34 | 10. [Multi-step Reasoning via Recurrent Dual Attention for Visual Dialog](https://arxiv.org/abs/1902.00579), ACL 2019 35 | 36 | 11. [Dual Attention Networks for Visual Reference Resolution in Visual Dialog](https://arxiv.org/abs/1902.09368), EMNLP 20219, [[]code](https://github.com/gicheonkang/dan-visdial) 37 | 38 | 12. [DMRM: A Dual-channel Multi-hop Reasoning Model for Visual Dialog](https://arxiv.org/abs/1912.08360), AAAI 2020, [[code]](https://github.com/phellonchen/DMRM) 39 | 40 | 13. [Modality-Balanced Models for Visual Dialogue](https://arxiv.org/abs/2001.06354), AAAI 2020 41 | 42 | 14. [DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue](https://arxiv.org/abs/1911.07251), AAAI 2020, [[code]](https://github.com/JXZe/DualVD) 43 | 44 | 15. [Two Causal Principles for Improving Visual Dialog](https://arxiv.org/abs/1911.10496), CVPR 2020, [[code]](https://github.com/simpleshinobu/visdial-principles) 45 | 46 | 16. [DAM: Deliberation, Abandon and Memory Networks for Generating Detailed and Non-repetitive Responses in Visual Dialogue](https://arxiv.org/abs/2007.03310), IJCAI 2020, [[code]](https://github.com/JXZe/DAM) 47 | 48 | 17. [KBGN: Knowledge-Bridge Graph Network for Adaptive Vision-Text Reasoning in Visual Dialogue](https://arxiv.org/abs/2008.04858), ACM MM 2020 49 | 50 | 18. [Large-scale Pretraining for Visual Dialog: A Simple State-of-the-Art Baseline](https://arxiv.org/abs/1912.02379), ECCV 2020, [[code]](https://github.com/vmurahari3/visdial-bert) 51 | 52 | 19. [Visual Dialog: Light-weight Transformer for Many Inputs](https://arxiv.org/abs/1911.11390), ECCV 2020, [[code]](https://github.com/davidnvq/visdial) 53 | 54 | 20. [Multi-View Attention Network for Visual Dialog](https://arxiv.org/abs/2004.14025), ACL 2020, [[code]](https://github.com/taesunwhang/MVAN-VisDial) 55 | 56 | 21. [History for Visual Dialog: Do we really need it?](https://aclanthology.org/2020.acl-main.728/), ACL 2020, [[code]](https://github.com/shubhamagarwal92/visdial_conv) 57 | 58 | 22. [VD-BERT: A Unified Vision and Dialog Transformer with BERT](https://arxiv.org/abs/2004.13278), EMNLP 2020, [[code]](https://github.com/salesforce/VD-BERT) 59 | 60 | 23. [GoG: Graph-over-Graph Network for Visual Dialog](https://aclanthology.org/2021.findings-acl.20/), ACL Findings 2021 61 | 62 | 24. [Multimodal Incremental Transformer for Visual Dialogue Generation](https://aclanthology.org/2021.findings-acl.38/), ACL Findings 2021 63 | 64 | 25. [Learning to Ground Visual Objects for Visual Dialog](https://arxiv.org/abs/2109.06013), EMNLP Findings 2021 65 | 66 | 26. [VU-BERT: A Unified framework for Visual Dialog](https://arxiv.org/abs/2202.10787), ICASSP 2022 67 | 68 | 27. [Improving Cross-Modal Understanding in Visual Dialog via Contrastive Learning](https://arxiv.org/abs/2204.07302), ICASSP 2022 69 | 70 | 28. [UTC: A Unified Transformer with Inter-Task Contrastive Learning for Visual Dialog](https://arxiv.org/abs/2205.00423), CVPR 2022 71 | 72 | 29. [Unsupervised and Pseudo-Supervised Vision-Language Alignment in Visual Dialog](https://arxiv.org/abs/2205.00423), ACM MM 2022 73 | 74 | ## GuessWhat 75 | [GuessWhat?! Visual object discovery through multi-modal dialogue](https://arxiv.org/abs/1611.08481), CVPR 2017, [[code]](https://github.com/GuessWhatGame/guesswhat) 76 | 77 | ## GuessWhich 78 | [Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning](https://arxiv.org/abs/1703.06585), ICCV 2017, [[code]](https://github.com/batra-mlp-lab/visdial-rl) 79 | 80 | # Video-based Visual Dialog 81 | 82 | [Bridging Text and Video: A Universal Multimodal Transformer for Video-Audio Scene-Aware Dialog](https://arxiv.org/abs/2002.00163), AAAI 2020, [[code]](https://github.com/ictnlp/DSTC8-AVSD) 83 | 84 | 85 | 86 | # Other Resources 87 | 88 | * [Visual Dialog Homepage](https://visualdialog.org/) 89 | * [Visual Dialog Challenge Startcode](https://github.com/batra-mlp-lab/visdial-challenge-starter-pytorch) 90 | 91 | --------------------------------------------------------------------------------