VOSR shows that competitive generative image super-resolution with faithful structures can be achieved by training a diffusion-style model from scratch on visual data alone, using a vision encoder for guidance and a restoration-oriented sampling strategy.
To- ward generalized image quality assessment: Relaxing the perfect reference quality assumption
2 Pith papers cite this work. Polarity classification is still indexing.
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Presents SPPE benchmark and ERMA/C2E-S2SER methods for editability assessment and surrogate-to-source recovery in MLLM privacy protection, reporting metric improvements.
citing papers explorer
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VOSR: A Vision-Only Generative Model for Image Super-Resolution
VOSR shows that competitive generative image super-resolution with faithful structures can be achieved by training a diffusion-style model from scratch on visual data alone, using a vision encoder for guidance and a restoration-oriented sampling strategy.
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When Recovery Matters: The Blind Spot of Surrogate Privacy in MLLM Editing
Presents SPPE benchmark and ERMA/C2E-S2SER methods for editability assessment and surrogate-to-source recovery in MLLM privacy protection, reporting metric improvements.