{"type":"ScholarlyArticle","title":"TG-VQA: Ternary Game of Video Question Answering","authors":[{"name":"Hao Li","slug":"hao-li","given":"Hao","family":"Li","affiliation":"School of Electronic and Computer Engineering , Peking University , Shenzhen , China; Shanghai AI Laboratory , Shanghai , China; AI for Science (AI4S)-Preferred Program , Peking University Shenzhen Graduate School"},{"name":"Peng Jin","slug":"peng-jin","given":"Peng","family":"Jin","affiliation":"School of Electronic and Computer Engineering , Peking University , Shenzhen , China; AI for Science (AI4S)-Preferred Program , Peking University Shenzhen Graduate School"},{"name":"Zesen Cheng","slug":"zesen-cheng","given":"Zesen","family":"Cheng","affiliation":"School of Electronic and Computer Engineering , Peking University , Shenzhen , China; AI for Science (AI4S)-Preferred Program , Peking University Shenzhen Graduate School"},{"name":"Songyang Zhang","slug":"songyang-zhang","given":"Songyang","family":"Zhang","affiliation":"Shanghai AI Laboratory , Shanghai , China"},{"name":"Kai Chen","slug":"kai-chen","given":"Kai","family":"Chen","affiliation":"Shanghai AI Laboratory , Shanghai , China"},{"name":"Zhennan Wang","slug":"zhennan-wang","given":"Zhennan","family":"Wang","affiliation":"Peng Cheng Laboratory , Shenzhen , China"},{"name":"Chang Liu","slug":"chang-liu","given":"Chang","family":"Liu","affiliation":"Department of Automation and BNRist , Tsinghua University"},{"name":"Jie Chen","slug":"jie-chen","given":"Jie","family":"Chen","affiliation":"School of Electronic and Computer Engineering , Peking University , Shenzhen , China; AI for Science (AI4S)-Preferred Program , Peking University Shenzhen Graduate School; Peng Cheng Laboratory , Shenzhen , China"}],"abstract":"Video question answering aims at answering a question about the video content by reasoning the alignment semantics within them. However, since relying heavily on human instructions, i.e., annotations or priors, current contrastive learning-based VideoQA methods remains challenging to perform fine-grained visual-linguistic alignments. In this work, we innovatively resort to game theory, which can simulate complicated relationships among multiple players with specific interaction strategies, e.g., video, question, and answer as ternary players, to achieve fine-grained alignment for VideoQA task. Specifically, we carefully design a VideoQA-specific interaction strategy to tailor the characteristics of VideoQA, which can mathematically generate the fine-grained visual-linguistic alignment label without label-intensive efforts. Our TG-VQA outperforms existing state-of-the-art by a large margin (more than 5%) on long-term and short-term VideoQA datasets, verifying its effectiveness and generalization ability. Thanks to the guidance of game-theoretic interaction, our model impressively convergences well on limited data (10^4 videos), surpassing most of those pre-trained on large-scale data (10^7 videos).","doi":"10.24963/ijcai.2023/116","url":"https://ijcai.org/proceedings/2023/116","pdf":"https://ijcai.org/proceedings/2023/0116.pdf","markdown":"https://ijcai.org/proceedings/2023/116.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/116","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"Computer Vision","track":"Main Track","number":116,"pages":{"first":1044,"last":1052},"keywords":["Computer Vision: CV: Video analysis and understanding","Computer Vision: CV: Visual reasoning and symbolic representation","Computer Vision: CV: Scene analysis and understanding"],"videos":[],"references":[{"position":1,"raw":"[Aflalo et al., 2022] Estelle Aflalo, Meng Du, Shao-Yen Tseng, Yongfei Liu, Chenfei Wu, Nan Duan, and Vasudev Lal. 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