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- Radu TimofteSuggested from co-authorship
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Works33 from public data
- Single-Model and Any-Modality for Video Object Tracking172
This work introduces Un-Track, a Unified Tracker of a single set of parameters for any modality, which surpasses both SOTA unified trackers and modality-specific counterparts, validating the effectiveness and practicality.
- NTIRE 2020 Challenge on NonHomogeneous Dehazing125
This paper reviews the NTIRE 2020 Challenge on Non-Homogeneous Dehazing of images (restoration of rich details in hazy image) and proposed solutions gauge the state-of-the-art in image dehazing.
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- NTIRE 2024 Challenge on Low Light Image Enhancement: Methods and Results85
This paper meticulously evaluates the state-of-the-art advancements in enhancing low-light images, reflecting the significant progress and creativity in this field.
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- Perceptual Image Enhancement for Smartphone Real-Time Applications40
This paper proposes LPIENet, a lightweight network for perceptual image enhancement, with the focus on deploying it on smartphones, and shows that, with much fewer parameters and operations, the model can deal with the mentioned artifacts and achieve competitive performance compared with state-of-the-art methods on standard benchmarks.
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- NTIRE 2025 Challenge on Low Light Image Enhancement: Methods and Results29
This paper thoroughly evaluates the state-of-the-art advancements in LLIE, showcasing the significant progress.
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- Ntire 2025 Image Shadow Removal Challenge Report22
This work examines the findings of the NTIRE 2025 Shadow Removal Challenge, with 17 teams successfully submitting their solutions during the final evaluation phase, and one focusing on reconstruction fidelity and the other on visual perception through a user study.
- Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey21
The NTIRE 2024 RAW Image Super-Resolution Challenge is reviewed, highlighting the proposed solutions and results, and providing a gauge for the current state-of-the-art in RAW Image Super-Resolution.
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- NTIRE 2026 Challenge on Single Image Reflection Removal in the Wild: Datasets, Results, and Methods20
The NTIRE 2026 challenge on single-image reflection removal (SIRR) in the wild is reviewed, with the top-ranked methods advanced the state-of-the-art reflection removal performance and earned unanimous recognition from five experts in the field.
- Bokehlicious: Photorealistic Bokeh Rendering with Controllable Apertures15
This work proposes Bokehlicious, a highly efficient network that provides intuitive control over Bokeh strength through an ApertureAware Attention mechanism, mimicking the physical lens aperture, achieving competitive results on the RealDOF benchmark.
- BSRAW: Improving Blind RAW Image Super-Resolution13
This work designs a realistic degradation pipeline tailored specifically for training models with raw sensor data that can upscale real-scene RAW images and improve their quality, and presents a new DSLM dataset and benchmark for this task.
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- AIM 2025 Rip Current Segmentation (RipSeg) Challenge Report9
This report presents an overview of the AIM 2025 RipSeg Challenge, a competition designed to advance techniques for automatic rip current segmentation in still images, and outlines the dataset details, competition framework, evaluation metrics, and final results.
- Toward Efficient Deep Blind Raw Image Restoration8
A new realistic degradation pipeline for training deep blind RAW restoration models that considers realistic sensor noise, motion blur, camera shake, and other common degradations and is considered to be the most exhaustive analysis on RAW image restoration.
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- After the Party: Navigating the Mapping from Color to Ambient Lighting4
CL3AN is introduced, the first large-scale, high-resolution dataset of its kind designed to facilitate the restoration of images captured under multiple Colored Light sources to their AmbientNormalized counterparts, and demonstrates enhanced robustness under non-homogeneous color lighting and material-specific reflectance variations, all while maintaining a highly competitive computational cost.
- AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results3
This paper thoroughly evaluates the state-of-the-art advances in high-FPS single image motion deblurring, showcasing the significant progress in the field, while leveraging samples of the novel dataset, MIORe, that introduces challenging examples of movement patterns.
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- A Simple Combination of Diffusion Models for Better Quality Trade-Offs in Image Denoising1
The proposed Linear Combination Diffusion Denoiser (LCDD), which unifies two complementary inference procedures-one that leverages the model's generative potential and another that ensures faithful signal recovery that ensures faithful signal recovery for additive Gaussian noise removal.
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Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-12. 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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