DiffIML applies score-based generative modeling to image manipulation localization, recovering coherent masks iteratively from noise to improve generalization on unseen manipulation types.
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5 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.CV 5years
2026 5representative citing papers
The paper releases SR-Ground, a crowdsourced dataset for pixel-level segmentation of six artifact types in super-resolved images, and shows its use for training grounded IQA models and artifact-reducing fine-tuning.
A multimodal CNN on 87,547 Vogue images classifies fashion houses at 78.2% top-1 accuracy, decades at 88.6%, and years at 58.3% with 2.2-year mean error, and shows texture and luminance carry most of the house-identity signal.
GTPBD-MM is the first multimodal benchmark for global terraced parcel extraction, integrating image, text, and DEM data with experiments showing that textual and terrain cues improve delineation accuracy over image-only approaches.
CrossWeaver introduces MIB and SAF modules to enable flexible, reliability-aware cross-modal interaction and fusion, achieving SOTA multimodal semantic segmentation with minimal parameters and generalization to unseen modality sets.
citing papers explorer
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Towards Generalized Image Manipulation Localization via Score-based Model
DiffIML applies score-based generative modeling to image manipulation localization, recovering coherent masks iteratively from noise to improve generalization on unseen manipulation types.
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SR-Ground: Image Quality Grounding for Super-Resolved Content
The paper releases SR-Ground, a crowdsourced dataset for pixel-level segmentation of six artifact types in super-resolved images, and shows its use for training grounded IQA models and artifact-reducing fine-tuning.
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FASH-iCNN: Making Editorial Fashion Identity Inspectable Through Multimodal CNN Probing
A multimodal CNN on 87,547 Vogue images classifies fashion houses at 78.2% top-1 accuracy, decades at 88.6%, and years at 58.3% with 2.2-year mean error, and shows texture and luminance carry most of the house-identity signal.
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GTPBD-MM: A Global Terraced Parcel and Boundary Dataset with Multi-Modality
GTPBD-MM is the first multimodal benchmark for global terraced parcel extraction, integrating image, text, and DEM data with experiments showing that textual and terrain cues improve delineation accuracy over image-only approaches.
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CrossWeaver: Cross-modal Weaving for Arbitrary-Modality Semantic Segmentation
CrossWeaver introduces MIB and SAF modules to enable flexible, reliability-aware cross-modal interaction and fusion, achieving SOTA multimodal semantic segmentation with minimal parameters and generalization to unseen modality sets.