Diffusion-based per-view harmonization for lighting-consistent object transfer between 3DGS scenes, using heterogeneous training data and final 3D consolidation.
How far can we go with imagenet for text-to-image generation?arXiv preprint arXiv:2502.21318, 2025
2 Pith papers cite this work. Polarity classification is still indexing.
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Attention Separation ablations show that gains from SRA to Self-Flow in diffusion transformers arise mainly from noise-dimension data augmentation rather than token-level self-supervision.
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Lighting-Consistent Object Transfer Across Radiance Fields
Diffusion-based per-view harmonization for lighting-consistent object transfer between 3DGS scenes, using heterogeneous training data and final 3D consolidation.
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From SRA to Self-Flow: Data Augmentation or Self-Supervision?
Attention Separation ablations show that gains from SRA to Self-Flow in diffusion transformers arise mainly from noise-dimension data augmentation rather than token-level self-supervision.