GarmentZoom trains one model to synthesize unaligned close-up details into full-view garment images across continuous scales 3-20x without per-instance tuning.
IEEE Transactions on Image Processing19(11), 2861–2873 (2010)
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 2years
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UNVERDICTED 2representative citing papers
Proposes the SFR framework and InfoSqueeze module to resolve Interest Entanglement by decoupling regression and perceptual objectives in image super-resolution through shared feature representations.
citing papers explorer
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GarmentZoom: Generating Zoomable Images from Garment Listings
GarmentZoom trains one model to synthesize unaligned close-up details into full-view garment images across continuous scales 3-20x without per-instance tuning.
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Interest Entanglement: The Hidden Barrier to Blind Super-Resolution Optimization
Proposes the SFR framework and InfoSqueeze module to resolve Interest Entanglement by decoupling regression and perceptual objectives in image super-resolution through shared feature representations.