A new large-scale triplet dataset and diffusion transformer model using coarse human masks deliver improved video virtual try-on quality and generalization in challenging real-world conditions.
Mixed citations
IEEE Trans
Mixed citation behavior. Most common role is background (33%).
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Pith papers citing it
Background
33% of classified citations
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2026 6representative citing papers
MetaSR adaptively orchestrates metadata in a DiT-based generative SR model to deliver up to 1 dB PSNR gains and 50% bitrate savings across diverse content and degradations.
Defines recoverability maps via dense synthetic degradation sweeps and two summary metrics to show AI restoration recovers license plates from ~93% of extreme angle parameter space, with geometry rather than model architecture as the binding limit.
ZID-Net decouples diffusion-based priors into a training-only head to create an efficient feed-forward network for single-image dehazing, reporting 40.75 dB PSNR on RESIDE and 19 ms inference.
DeepSignature embeds digitally signed content-encoding watermarks via neural networks for robust image authentication, source attribution, and latent-space tamper localization.
ACPO uses anchor-based regularization with NR-IQA guidance to enable stable perceptual quality improvements in diffusion model fine-tuning.
citing papers explorer
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Mapping License Plate Recoverability Under Extreme Viewing Angles for Opportunistic Urban Sensing
Defines recoverability maps via dense synthetic degradation sweeps and two summary metrics to show AI restoration recovers license plates from ~93% of extreme angle parameter space, with geometry rather than model architecture as the binding limit.
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ACPO: Anchor-Constrained Perceptual Optimization for Diffusion Models with No-Reference Quality Guidance
ACPO uses anchor-based regularization with NR-IQA guidance to enable stable perceptual quality improvements in diffusion model fine-tuning.