activity
20242026
most citedNTIRE 2025 Challenge on Image Super-Resolution (x4): Methods and Results

2 citations · 2 across the 13 of their papers we have counts for

collaborators

15 papers

cs.CV2026

CLEAR: Conflict-aware Learning via Evidence-guided Adaptive Routing for Unified Sparse-View 3D Gaussian Super-Resolution

Hantang Li, Qiang Zhu, Xiandong Meng +2

Sparse-view 3D Gaussian Splatting Super-resolution is highly challenging since the sparse and low-resolution (LR) inputs lack sufficient geometric and high-frequency information fo…

cs.CV2026

PairDropGS: Paired Dropout-Induced Consistency Regularization for Sparse-View Gaussian Splatting

Hantang Li, Qiang Zhu, Xiandong Meng +3

Dropout-based sparse-view 3D Gaussian Splatting (3DGS) methods alleviate overfitting by randomly suppressing Gaussian primitives during training. Existing methods mainly focus on d…

cs.CV2026

NTIRE 2026 3D Restoration and Reconstruction in Real-world Adverse Conditions: RealX3D Challenge Results

Shuhong Liu, Chenyu Bao, Ziteng Cui +103

This paper presents a comprehensive review of the NTIRE 2026 3D Restoration and Reconstruction (3DRR) Challenge, detailing the proposed methods and results. The challenge seeks to…

cs.CV2026

DOC-GS: Dual-Domain Observation and Calibration for Reliable Sparse-View Gaussian Splatting

Hantang Li, Qiang Zhu, Xiandong Meng +2

Sparse-view reconstruction with 3D Gaussian Splatting (3DGS) is fundamentally ill-posed due to insufficient geometric supervision, often leading to severe overfitting and the emerg…

cs.CV2026

LG-HCC: Local Geometry-Aware Hierarchical Context Compression for 3D Gaussian Splatting

Xuan Deng, Xiandong Meng, Hengyu Man +4

Although 3D Gaussian Splatting (3DGS) enables high-fidelity real-time rendering, its prohibitive storage overhead severely hinders practical deployment. Recent anchor-based 3DGS co…

cs.CV2025

Trajectory-aware Shifted State Space Models for Online Video Super-Resolution

Qiang Zhu, Xiandong Meng, Yuxian Jiang +5

Online video super-resolution (VSR) is an important technique for many real-world video processing applications, which aims to restore the current high-resolution video frame based…

eess.IV2025

Compressed Video Super-Resolution based on Hierarchical Encoding

Yuxuan Jiang, Siyue Teng, Qiang Zhu +6

This paper presents a general-purpose video super-resolution (VSR) method, dubbed VSR-HE, specifically designed to enhance the perceptual quality of compressed content. Targeting s…

eess.IV2025

NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement: Methods and Results

Xin Li, Kun Yuan, Bingchen Li +110

This paper presents a review for the NTIRE 2025 Challenge on Short-form UGC Video Quality Assessment and Enhancement. The challenge comprises two tracks: (i) Efficient Video Qualit…

cs.CV2025

The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report

Bin Ren, Hang Guo, Lei Sun +143

This paper presents a comprehensive review of the NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution (ESR). The challenge aimed to advance the development of deep mode…

cs.CV2025★ 2 cited

NTIRE 2025 Challenge on Image Super-Resolution (x4): Methods and Results

Zheng Chen, Kai Liu, Jue Gong +108

This paper presents the NTIRE 2025 image super-resolution (4) challenge, one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025. The challenge aims to r…

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.CV2025

FCVSR: A Frequency-aware Method for Compressed Video Super-Resolution

Qiang Zhu, Fan Zhang, Feiyu Chen +3

Compressed video super-resolution (SR) aims to generate high-resolution (HR) videos from the corresponding low-resolution (LR) compressed videos. Recently, some compressed video SR…

eess.IV2024

OAPT: Offset-Aware Partition Transformer for Double JPEG Artifacts Removal

Qiao Mo, Yukang Ding, Jinhua Hao +5

Deep learning-based methods have shown remarkable performance in single JPEG artifacts removal task. However, existing methods tend to degrade on double JPEG images, which are prev…

cs.CV2024

Compressed Video Quality Enhancement with Temporal Group Alignment and Fusion

Qiang Zhu, Yajun Qiu, Yu Liu +2

In this paper, we propose a temporal group alignment and fusion network to enhance the quality of compressed videos by using the long-short term correlations between frames. The pr…

eess.IV2024

CPGA: Coding Priors-Guided Aggregation Network for Compressed Video Quality Enhancement

Qiang Zhu, Jinhua Hao, Yukang Ding +5

Recently, numerous approaches have achieved notable success in compressed video quality enhancement (VQE). However, these methods usually ignore the utilization of valuable coding…