The Dialog Must Go On: Improving Visual Dialog via Generative Self-Training
Author:
Affiliation:
1. Seoul National University,IPAI
2. NAVER AI Lab
3. NAVER Cloud CLOVA
Funder
Institute of Information & Communications Technology Planning & Evaluation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203535.pdf?arnumber=10203535
Reference86 articles.
1. Guess-what?! visual object discovery through multi-modal dialogue;de vries;CVPR,0
2. Multimodal Differential Network for Visual Question Generation
3. Visual Dialog
4. Video Captioning with Transferred Semantic Attributes
5. An image is worth 16x16 words: Transformers for image recognition at scale;dosovitskiy;ICLRE,0
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2. PROGrasp: Pragmatic Human-Robot Communication for Object Grasping;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
3. VD-GR: Boosting Visual Dialog with Cascaded Spatial-Temporal Multi-Modal GRaphs;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03
4. Modeling Intra- and Inter-Modal Alignment with Optimal Transport for Visual Dialog;2023 IEEE 35th International Conference on Tools with Artificial Intelligence (ICTAI);2023-11-06
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