Institute of Computing Technology, Chinese Academy IR
CRIC: A VQA Dataset for Compositional Reasoning on Vision and Commonsense | |
Gao, Difei; Wang, Ruiping; Shan, Shiguang; Chen, Xilin | |
2023-05-01 | |
发表期刊 | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE |
ISSN | 0162-8828 |
卷号 | 45期号:5页码:5561-5578 |
摘要 | Alternatively inferring on the visual facts and commonsense is fundamental for an advanced visual question answering (VQA) system. This ability requires models to go beyond the literal understanding of commonsense. The system should not just treat objects as the entrance to query background knowledge, but fully ground commonsense to the visual world and imagine the possible relationships between objects, e.g., "fork, can lift, food". To comprehensively evaluate such abilities, we propose a VQA benchmark, Compositional Reasoning on vIsion and Commonsense(CRIC), which introduces new types of questions about CRIC, and an evaluation metric integrating the correctness of answering and commonsense grounding. To collect such questions and rich additional annotations to support the metric, we also propose an automatic algorithm to generate question samples from the scene graph associated with the images and the relevant knowledge graph. We further analyze several representative types of VQA models on the CRIC dataset. Experimental results show that grounding the commonsense to the image region and joint reasoning on vision and commonsense are still challenging for current approaches. The dataset is available at https://cricvqa.github.io. |
关键词 | Visualization Task analysis Tail Head Annotations Magnetic heads Mouth Visual question answering compositional reasoning commonsense reasoning dataset construction |
DOI | 10.1109/TPAMI.2022.3210780 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key R&D Program of China[2021ZD0111901] ; Natural Science Foundation of China[U21B2025] ; Natural Science Foundation of China[U19B2036] ; Natural Science Foundation of China[61922080] |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000964792800015 |
出版者 | IEEE COMPUTER SOC |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/21408 |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Wang, Ruiping |
作者单位 | Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Gao, Difei,Wang, Ruiping,Shan, Shiguang,et al. CRIC: A VQA Dataset for Compositional Reasoning on Vision and Commonsense[J]. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,2023,45(5):5561-5578. |
APA | Gao, Difei,Wang, Ruiping,Shan, Shiguang,&Chen, Xilin.(2023).CRIC: A VQA Dataset for Compositional Reasoning on Vision and Commonsense.IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE,45(5),5561-5578. |
MLA | Gao, Difei,et al."CRIC: A VQA Dataset for Compositional Reasoning on Vision and Commonsense".IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 45.5(2023):5561-5578. |
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