Is this you? Claim this profile to correct it, add a bio and choose the work people see first.
Claim this profileWorks65 from public data
- 254
- 211
- 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.
- 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.
- NTIRE 2024 Challenge on Image Super-Resolution (×4): Methods and Results83
This paper reviews the NTIRE 2024 challenge on image super-resolution (×4), highlighting the solutions proposed and the outcomes obtained, and offers a comprehensive overview of current trends in this field.
- 79
- 64
- 59
- 52
- A Coarse-to-Fine Multi-stream Hybrid Deraining Network for Single Image Deraining49
A new coarse-to-fine single image deraining framework termed Multi-stream Hybrid Deraining Network (shortly, MH-DerainNet) is proposed, which combines the SSIM loss and perceptual loss to preserve the per-pixel similarity as well as preserving the global structures so that the deraining result is more accurate.
- 46
- 42
- The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report39
This paper presents a comprehensive review of the NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution, emphasizing groundbreaking advancements in state-of-the-art single-image ESR techniques.
- 39
- Motion Matters: Motion-guided Modulation Network for Skeleton-based Micro-Action Recognition37
A novel Motion-guided Modulation Network (MMN) is presented that implicitly captures and modulates subtle motion cues to enhance spatial-temporal representation learning and achieves state-of-the-art performance in skeleton-based micro-action recognition.
- 37
- SGINet: Toward Sufficient Interaction Between Single Image Deraining and Semantic Segmentation35
A Semantic Guided Interactive Network (SGINet), which considers the sufficient interaction between SID and semantic segmentation using a three-stage deraining manner, i.e., coarse deraining, semantic information extraction, and semantics guided deraining.
- The Tenth NTIRE 2025 Image Denoising Challenge Report34
An overview of the NTIRE 2025 Image Denoising Challenge is presented, highlighting the proposed methodologies and corresponding results, providing insights into the current state-of-the-art in image denoising.
- 31
- Temporal-Frequency State Space Duality: An Efficient Paradigm for Speech Emotion Recognition29
TF-Mamba, a novel multi-domain framework that captures emotional expressions in both temporal and frequency dimensions, achieves an optimal balance between computational efficiency and model expressiveness for Speech Emotion Recognition (SER).
- 29
- Robust Attention Deraining Network for Synchronous Rain Streaks and Raindrops Removal27
This paper proposes a new and universal SID model with novel modules, termed Robust Attention Deraining Network (RadNet), with strong robustness and generalization ability, and demonstrates that this RadNet could outperform other state-of-the-art SID methods.
- Raw Image Reconstruction From Rgb on Smartphones. Ntire 2025 Challenge Report23
This paper aims to recover RAW sensor images from smartphones given the corresponding sRGB images without metadata and, by doing this, “reverse” the ISP transformation.
- Micro-gesture Online Recognition using Learnable Query Points23
The solution developed by the team, HFUT-VUT, for the Micro-gesture Online Recognition track in the MiGA challenge at IJCAI 2024 ranks 2nd in the Micro-gesture Online Recognition track.
- 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.
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.