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- Rong WangSuggested from co-authorship
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Works62 from public data
- CoSeR: Bridging Image and Language for Cognitive Super-Resolution93
The Cognitive Super-Resolution (CoSeR) framework is introduced, empowering SR models with the capacity to comprehend low-resolution images and a novel condition injection scheme called “Ali-in-Attention ”, consolidating all conditional information into a single module.
- The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report91
This paper provides a comprehensive review of the NTIRE 2024 challenge, focusing on efficient single-image super-resolution (ESR) solutions and their outcomes, and gauge the state-of-the-art in efficient single-image super-resolution.
- Degradation-Guided One-Step Image Super-Resolution with Diffusion Priors78
This work introduced a novel one-step SR model, which significantly addresses the efficiency issue of diffusion-based SR methods and tailor a novel training pipeline by introducing an online negative sample generation strategy.
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- Dual Prompting Image Restoration with Diffusion Transformers33
This paper introduces DPIR (Dual Prompting Image Restoration), a novel image restoration method that effectivly extracts conditional information of low-quality images from multiple perspectives and delivers superior image restoration performance.
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- The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview20
A review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the resulting outcomes and offering an in-depth overview of the latest trends in the field.
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- Grounding-IQA: Grounding Multimodal Language Model for Image Quality Assessment17
This work introduces a new image quality assessment (IQA) task paradigm, **grounding-IQA**, which integrates multimodal referring and grounding with IQA to realize more fine-grained quality perception, thereby extending existing IQA.
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- Fuse Your Latents: Video Editing with Multi-source Latent Diffusion Models9
This paper is the first to reveal that T2I and T2V LDMs can complement each other in terms of structure and temporal consistency, ultimately generating high-quality videos.
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- Unsupervised Diffusion-Based Degradation Modeling for Real-World Super-Resolution5
This paper proposes an unsupervised diffusion-based degradation modeling framework (UDDM) to effectively capture real-world degradation distributions and introduces a physics-based dynamic degradation module (P-DDM) that adaptively models content-aware degradation, ensuring both content and structural accuracy.
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Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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