activity
20192026
most citedMulti-Scale Boosted Dehazing Network with Dense Feature Fusion

63 citations · 67 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

DNF-SR: Dual-Input and Negative-Aware Feature Fine-Tuning for Real-World Image Super-Resolution

Shuhao Han, Wenjie Liao, Hayden Vance +4

Benefiting from the powerful generative priors of diffusion models, diffusion-based real-world image super-resolution (Real-ISR) methods have demonstrated impressive performance.To…

cs.CV2026

DreamSR: Towards Ultra-High-Resolution Image Super-Resolution via a Receptive-Field Enhanced Diffusion Transformer

Qingji Dong, Hang Dong, Mingqin Chen +2

Large-scale pre-trained diffusion models have been extensively adopted for real-world image Super-Resolution because of their powerful generative priors through textual guidance. H…

cs.CV2025

Changes in Gaza: DINOv3-Powered Multi-Class Change Detection for Damage Assessment in Conflict Zones

Kai Zheng, Zhenkai Wu, Fupeng Wei +6

Accurately and swiftly assessing damage from conflicts is crucial for humanitarian aid and regional stability. In conflict zones, damaged zones often share similar architectural st…

cs.CV2024

PatchScaler: An Efficient Patch-Independent Diffusion Model for Image Super-Resolution

Yong Liu, Hang Dong, Jinshan Pan +5

While diffusion models significantly improve the perceptual quality of super-resolved images, they usually require a large number of sampling steps, resulting in high computational…

cs.CV2023★ 1 cited

Unfolding Once is Enough: A Deployment-Friendly Transformer Unit for Super-Resolution

Yong Liu, Hang Dong, Boyang Liang +6

Recent years have witnessed a few attempts of vision transformers for single image super-resolution (SISR). Since the high resolution of intermediate features in SISR models increa…

cs.CV2022

Boosting Video Super Resolution with Patch-Based Temporal Redundancy Optimization

Yuhao Huang, Hang Dong, Jinshan Pan +5

The success of existing video super-resolution (VSR) algorithms stems mainly exploiting the temporal information from the neighboring frames. However, none of these methods have di…

cs.CV2022

NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results

Ren Yang, Radu Timofte, Meisong Zheng +75

This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…

eess.IV2021

Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring

Chao Zhu, Hang Dong, Jinshan Pan +4

The success of the state-of-the-art video deblurring methods stems mainly from implicit or explicit estimation of alignment among the adjacent frames for latent video restoration.…

cs.CV2020★ 63 cited

Multi-Scale Boosted Dehazing Network with Dense Feature Fusion

Hang Dong, Jinshan Pan, Lei Xiang +4

In this paper, we propose a Multi-Scale Boosted Dehazing Network with Dense Feature Fusion based on the U-Net architecture. The proposed method is designed based on two principles,…

eess.IV2019★ 3 cited

AIM 2019 Challenge on Image Demoireing: Methods and Results

Shanxin Yuan, Radu Timofte, Gregory Slabaugh +25

This paper reviews the first-ever image demoireing challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ICCV 2019. This paper desc…