ImageAttributionBench is a benchmark dataset demonstrating that state-of-the-art image attribution methods lack robustness to image degradation and fail to generalize to semantically disjoint domains.
Fake artificial intelligence generated contents (faigc): A survey of theories, detection methods, and opportunities
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MG-RWKV combines bidirectional RWKV, multi-granularity mixture of experts, and cross-granularity consistency to achieve state-of-the-art temporal forgery localization with linear complexity.
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ImageAttributionBench: How Far Are We from Generalizable Attribution?
ImageAttributionBench is a benchmark dataset demonstrating that state-of-the-art image attribution methods lack robustness to image degradation and fail to generalize to semantically disjoint domains.
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MG-RWKV: Multi-Grained Context-Aware RWKV for Temporal Forgery Localization
MG-RWKV combines bidirectional RWKV, multi-granularity mixture of experts, and cross-granularity consistency to achieve state-of-the-art temporal forgery localization with linear complexity.