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This paper explicitly model and learn correlations between views by utilizing the covariance structure of posterior estimation errors during aggregation, demonstrating the need to go beyond the independence assumption in IMVC.
This work proposes EC\textsuperscript{2}Face, a multimodal face synthesis framework that improves semantic alignment through explicit semantic supervision and distribution-aware optimization, and introduces Explicit Conditional Consistency Guidance (ECCG), which imposes direct consistency supervision in pixel space.
FaceVid-Forensics-100K is introduced, a large-scale deepfake video dataset comprising 100,000 videos and spanning 33 synthesis methods across face swapping, face reenactment, and entire-face synthesis, and a multi-agent forensic reasoning framework that employs four specialized domain-expert agents to independently ana...
UCF-Net is proposed, an uncertainty-aware cascaded fusion network that harnesses CLIP's language-aligned semantic priors and DINO's self-supervised visual-structure priors and achieves the best mean AUC among the evaluated methods in both in-domain and cross-domain evaluations.
A compact classifier is trained to rank omitted sentences by whether they are needed to interpret retained text and reinsert the top-ranked candidates without support annotations at inference, training a compact classifier to optimize both relevance and referential completeness.
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