Visual Commonsense Causal Reasoning From a Still Image

Even from a still image, humans exhibit the ability to ratiocinate diverse visual cause-and-effect relationships of events preceding, succeeding, and extending beyond the given image scope. Previous work on commonsense causal reasoning (CCR) aimed at understanding general causal dependencies among c...

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Vydané v:IEEE access Ročník 13; s. 85084 - 85097
Hlavní autori: Wu, Xiaojing, Guo, Rui, Li, Qin, Zhu, Ning
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Cause effect analysis
Commonsense reasoning
Correlation
Electronic mail
Estimation
Large language models
multimodal large language model
Natural languages
Question answering (information retrieval)
Reasoning
Visual commonsense reasoning
Visual effects
visual event reasoning
Visualization
ISSN:2169-3536, 2169-3536
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Popis
Shrnutí:Even from a still image, humans exhibit the ability to ratiocinate diverse visual cause-and-effect relationships of events preceding, succeeding, and extending beyond the given image scope. Previous work on commonsense causal reasoning (CCR) aimed at understanding general causal dependencies among common events in natural language descriptions. However, in real-world scenarios, CCR is fundamentally a multisensory task and is more susceptible to spurious correlations, given that commonsense causal relationships manifest in various modalities and involve multiple sources of confounders. In this work, to the best of our knowledge, we present the first comprehensive study focusing on visual commonsense causal reasoning (VCCR) within the potential outcomes framework. By drawing parallels between vision-language data and human subjects in the observational study, we tailor a foundational framework, VCC-Reasoner, for detecting implicit visual commonsense causation. It combines inverse propensity score weighting and outcome regression, offering dual robust estimates of the average treatment effect. Empirical evidence underscores the efficacy and superiority of VCC-Reasoner, showcasing its outstanding VCCR capabilities.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2025.3558429