Different Changes Require Different Reasoning: Change-Type-Specialized Experts for Robust Change Captioning
Change captioning is the task of generating natural language descriptions that explain the changes between a pair of images. Although different change types (e.g., color shifts, object additions) exhibit distinct visual cues and require specialized reasoning processes, existing methods often overlook these distinctions. To address this limitation, we propose Multi-Expert Diagnosis for Image Change (MEDIC), a novel framework that introduces change-type awareness by explicitly modeling change categories. MEDIC employs type-specialized memory experts that dynamically retrieve type-relevant visual patterns conditioned on the input. This design enables each expert to capture diverse variations...
| Authors | Jiyoung Park, InJae Oh, Jung Uk Kim |
|---|---|
| Primary category | cs.CV |
| Published | 1 September 2026 |
| Last updated at source | 1 September 2026 |
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