Immune2V immunizes images against dual-stream I2V generation by enforcing temporally balanced latent divergence and aligning generative features to a precomputed collapse trajectory, yielding stronger persistent degradation than image-level baselines.
Denoising diffusion probabilistic models.Ad- vances in neural information processing systems, 33:6840–6851
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LiBaGS scores and selects synthetic data near decision boundaries using proximity, uncertainty, density, and validity, with boundary-gap allocation and marginal stopping to improve training accuracy.
3DTV proposes a feedforward network for real-time sparse-view interpolation using Delaunay triplet selection and a pose-aware coarse-to-fine depth module, outperforming real-time baselines without scene-specific optimization.
citing papers explorer
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Immune2V: Image Immunization Against Dual-Stream Image-to-Video Generation
Immune2V immunizes images against dual-stream I2V generation by enforcing temporally balanced latent divergence and aligning generative features to a precomputed collapse trajectory, yielding stronger persistent degradation than image-level baselines.
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LiBaGS: Lightweight Boundary Gap Synthesis for Targeted Synthetic Data Selection
LiBaGS scores and selects synthetic data near decision boundaries using proximity, uncertainty, density, and validity, with boundary-gap allocation and marginal stopping to improve training accuracy.
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3DTV: A Feedforward Interpolation Network for Real-Time View Synthesis
3DTV proposes a feedforward network for real-time sparse-view interpolation using Delaunay triplet selection and a pose-aware coarse-to-fine depth module, outperforming real-time baselines without scene-specific optimization.