A single transformer model using a new markup representation generates functional floorplans from diverse conditions and outperforms prior task-specific methods on the RPLAN dataset.
Denoising diffu- sion probabilistic models
6 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 6representative citing papers
PhySe-RPO enables diffusion-based surgical smoke removal by converting restoration into a stochastic policy optimized with physics consistency and CLIP semantic rewards under limited supervision.
UniGenDet unifies generative and discriminative models through symbiotic self-attention and detector-guided alignment to co-evolve image generation and authenticity detection.
The NTIRE 2026 challenge establishes a benchmark for x4 super-resolution of remote sensing infrared images, with 13 teams submitting valid methods evaluated on a dedicated dataset.
The NTIRE 2026 mobile real-world image super-resolution challenge received 16 valid submissions and overviews methods balancing image quality with mobile execution speed.
citing papers explorer
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Unified Vector Floorplan Generation via Markup Representation
A single transformer model using a new markup representation generates functional floorplans from diverse conditions and outperforms prior task-specific methods on the RPLAN dataset.
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PhySe-RPO: Physics and Semantics Guided Relative Policy Optimization for Diffusion-Based Surgical Smoke Removal
PhySe-RPO enables diffusion-based surgical smoke removal by converting restoration into a stochastic policy optimized with physics consistency and CLIP semantic rewards under limited supervision.
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UniGenDet: A Unified Generative-Discriminative Framework for Co-Evolutionary Image Generation and Generated Image Detection
UniGenDet unifies generative and discriminative models through symbiotic self-attention and detector-guided alignment to co-evolve image generation and authenticity detection.
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The First Challenge on Remote Sensing Infrared Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview
The NTIRE 2026 challenge establishes a benchmark for x4 super-resolution of remote sensing infrared images, with 13 teams submitting valid methods evaluated on a dedicated dataset.
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The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview
The NTIRE 2026 mobile real-world image super-resolution challenge received 16 valid submissions and overviews methods balancing image quality with mobile execution speed.
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