Is this you? Claim this profile to correct it, add a bio and choose the work people see first.
Claim this profileWorks69 from public data
- NTIRE 2020 Challenge on Real-World Image Super-Resolution: Methods and Results191
The NTIRE 2020 challenge addresses the real world setting, where paired true high and low-resolution images are unavailable, and the ultimate goal is to achieve the best perceptual quality, evaluated using a human study.
- 137
- 113
- 92
- 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.
- 74
- 58
- 56
- 45
- AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results43
This paper introduces the real image Super-Resolution challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020, and gauges the state-of-the-art approaches for real image SR in terms of PSNR and SSIM.
- 42
- 39
- 33
- 30
- 26
- NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge24
This challenge established a new benchmark for real-world image restoration, featuring diverse scenarios with and without reference ground truth, and tasked participants with restoring real-captured images suffering from complex and unknown degradations.
- 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.
- NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: AI Flash Portrait (Track 3)19
A comprehensive overview of the NTIRE 2026 3rd Restore Any Image Model (RAIM) challenge, with a specific focus on Track 3: AI Flash Portrait, and comprehensively evaluates the proposed algorithms utilizing a hybrid evaluation system that integrates objective quantitative metrics with rigorous subjective assessment protocols.
- Using less annotation workload to establish a pathological auxiliary diagnosis system for gastric cancer17
To help pathologists improve diagnostic accuracy and efficiency, 1,514 cases of stomach H&E-stained specimens with complete diagnostic information are collected to establish a pathological auxiliary diagnosis system based on deep learning.
- Structurally sophisticated 3D-printed PCL-fibrin hydrogel meniscal scaffold promotes in situ regeneration in the rabbit knee meniscus14
The integration of 3D printing technology and the Fib hydrogel provided a supportive microenvironment for chondrocyte proliferation and ECM secretion, facilitating the in situ regeneration and repair of the meniscal defect.
- 11
- High-strength and high-elasticity silk fibroin-composite gelatin biomaterial hydrogels for rabbit knee cartilage regeneration10
It is established that high-strength SF/Gel hydrogel prepared by applying the binary-solvent-induced conformation transition strategy has potential applications in cartilage tissue repair and regeneration and is a feasible biomaterial for osteochondral regeneration.
- 9
- A blind image super-resolution network guided by kernel estimation and structural prior knowledge8
This work proposes a two stage blind super-resolution network that is based on kernel estimation strategy and is capable of integrating structural texture as prior knowledge and outperforms the state-of-the-art methods in terms of fidelity and recovery of clear details.
- Integrated strategies in meniscus tissue engineering: from biomaterials to stem cell–driven regeneration7
Recent advances in scaffold design and cell-based therapies for meniscus repair are summarized and the convergence of materials science, stem cell biology, advanced fabrication, and computational modeling offers a promising roadmap toward clinically viable meniscus regeneration.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. 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.
Report an error
Wrong papers, two people merged into one, or a profile that should not be here? Tell us and we will fix or hide it.