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20242026
most citedMTKD: Multi-Teacher Knowledge Distillation for Image Super-Resolution

28 citations · 70 across the 18 of their papers we have counts for

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13 papers · 1 filter

cs.CV2026

Beyond Source Prompts: Towards Visually Grounded AI-Generated Video Quality Assessment

Kehao Zhou, Yixuan Li, Yuxuan Jiang +1

Recent advances in generative artificial intelligence have accelerated video generation technologies. However, AI-generated videos (AIGVs) remain susceptible to various distortions…

cs.CV2026

The First Challenge on Mobile Real-World Image Super-Resolution at NTIRE 2026: Benchmark Results and Method Overview

Jiatong Li, Zheng Chen, Kai Liu +91

This paper provides a review of the NTIRE 2026 challenge on mobile real-world image super-resolution, highlighting the proposed solutions and the resulting outcomes. The challenge…

cs.CV2026

The Fourth Challenge on Image Super-Resolution (4) at NTIRE 2026: Benchmark Results and Method Overview

Zheng Chen, Kai Liu, Jingkai Wang +150

This paper presents the NTIRE 2026 image super-resolution (4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to r…

cs.CV2026

The Second Challenge on Real-World Face Restoration at NTIRE 2026: Methods and Results

Jingkai Wang, Jue Gong, Zheng Chen +50

This paper provides a review of the NTIRE 2026 challenge on real-world face restoration, highlighting the proposed solutions and the resulting outcomes. The challenge focuses on ge…

cs.CV2026

NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models: Datasets, Methods and Results

Xin Li, Jiachao Gong, Xijun Wang +75

This paper presents an overview of the NTIRE 2026 Challenge on Short-form UGC Video Restoration in the Wild with Generative Models. This challenge utilizes a new short-form UGC (S-…

cs.CV2026

Q-Tacit: Image Quality Assessment via Latent Visual Reasoning

Yuxuan Jiang, Yixuan Li, Hanwei Zhu +3

Vision-Language Model (VLM)-based image quality assessment (IQA) has been significantly advanced by incorporating Chain-of-Thought (CoT) reasoning. Recent work has refined image qu…

cs.CV2025

EfficientSAM3: Progressive Hierarchical Distillation for Video Concept Segmentation from SAM1, 2, and 3

Chengxi Zeng, Yuxuan Jiang, Aaron Zhang

The Segment Anything Model 3 (SAM3) advances visual understanding with Promptable Concept Segmentation (PCS) across images and videos, but its unified architecture (shared vision b…

cs.CV2025

GFix: Perceptually Enhanced Gaussian Splatting Video Compression

Siyue Teng, Ge Gao, Duolikun Danier +5

3D Gaussian Splatting (3DGS) enhances 3D scene reconstruction through explicit representation and fast rendering, demonstrating potential benefits for various low-level vision task…

cs.CV2025

Instance Data Condensation for Image Super-Resolution

Tianhao Peng, Ho Man Kwan, Yuxuan Jiang +5

Deep learning based Image Super-Resolution (ISR) relies on large training datasets to optimize model generalization; this requires substantial computational and storage resources d…

cs.CV2025

Agglomerating Large Vision Encoders via Distillation for VFSS Segmentation

Chengxi Zeng, Yuxuan Jiang, Fan Zhang +2

The deployment of foundation models for medical imaging has demonstrated considerable success. However, their training overheads associated with downstream tasks remain substantial…

cs.CV2025

C2D-ISR: Optimizing Attention-based Image Super-resolution from Continuous to Discrete Scales

Yuxuan Jiang, Chengxi Zeng, Siyue Teng +4

In recent years, attention mechanisms have been exploited in single image super-resolution (SISR), achieving impressive reconstruction results. However, these advancements are stil…

cs.CV2025

Blind Video Super-Resolution based on Implicit Kernels

Qiang Zhu, Yuxuan Jiang, Shuyuan Zhu +3

Blind video super-resolution (BVSR) is a low-level vision task which aims to generate high-resolution videos from low-resolution counterparts in unknown degradation scenarios. Exis…

cs.CV2024★ 15 cited

HIIF: Hierarchical Encoding based Implicit Image Function for Continuous Super-resolution

Yuxuan Jiang, Ho Man Kwan, Tianhao Peng +5

Recent advances in implicit neural representations (INRs) have shown significant promise in modeling visual signals for various low-vision tasks including image super-resolution (I…