3 citations · 10 across the 24 of their papers we have counts for
26 papers
OmniVR: Audio-Video Conditional Generation for Archival Footage Restoration
Xin Lu, Zihao Fan, Mingchen Zhong +4
Archival footage often suffers from coupled visual and acoustic degradations, yet most restoration systems process the two modalities separately. To address this problem, we presen…
GS-STVSR: Ultra-Efficient Continuous Spatio-Temporal Video Super-Resolution via 2D Gaussian Splatting
Mingyu Shi, Xin Di, Long Peng +8
Continuous Spatio-Temporal Video Super-Resolution (C-STVSR) aims to simultaneously enhance the spatial resolution and frame rate of videos by arbitrary scale factors, offering grea…
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…
Iterative Inference-time Scaling with Adaptive Frequency Steering for Image Super-Resolution
Hexin Zhang, Dong Li, Jie Huang +3
Diffusion models have become a leading paradigm for image super-resolution (SR), but existing methods struggle to guarantee both the high-frequency perceptual quality and the low-f…
FinPercep-RM: A Fine-grained Reward Model and Co-evolutionary Curriculum for RL-based Real-world Super-Resolution
Yidi Liu, Zihao Fan, Jie Huang +6
Reinforcement Learning with Human Feedback (RLHF) has proven effective in image generation field guided by reward models to align human preferences. Motivated by this, adapting RLH…
Latent Harmony: Synergistic Unified UHD Image Restoration via Latent Space Regularization and Controllable Refinement
Yidi Liu, Xueyang Fu, Jie Huang +5
Ultra-High Definition (UHD) image restoration faces a trade-off between computational efficiency and high-frequency detail retention. While Variational Autoencoders (VAEs) improve…
VisionSelector: End-to-End Learnable Visual Token Compression for Efficient Multimodal LLMs
Jiaying Zhu, Yurui Zhu, Xin Lu +5
Multimodal Large Language Models (MLLMs) encounter significant computational and memory bottlenecks from the massive number of visual tokens generated by high-resolution images or…
AIM 2025 challenge on Inverse Tone Mapping Report: Methods and Results
Chao Wang, Francesco Banterle, Bin Ren +25
This paper presents a comprehensive review of the AIM 2025 Challenge on Inverse Tone Mapping (ITM). The challenge aimed to push forward the development of effective ITM algorithms…
AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
George Ciubotariu, Florin-Alexandru Vasluianu, Zhuyun Zhou +44
This paper presents a comprehensive review of the AIM 2025 High FPS Non-Uniform Motion Deblurring Challenge, highlighting the proposed solutions and final results. The objective of…
AIM 2025 Low-light RAW Video Denoising Challenge: Dataset, Methods and Results
Alexander Yakovenko, George Chakvetadze, Ilya Khrapov +17
This paper reviews the AIM 2025 (Advances in Image Manipulation) Low-Light RAW Video Denoising Challenge. The task is to develop methods that denoise low-light RAW video by exploit…
PAID: Pairwise Angular-Invariant Decomposition for Continual Test-Time Adaptation
Kunyu Wang, Xueyang Fu, Yuanfei Bao +4
Continual Test-Time Adaptation (CTTA) aims to online adapt a pre-trained model to changing environments during inference. Most existing methods focus on exploiting target data, whi…
Fractional-order Spiking Neural Network
Chengjie Ge, Yufeng Peng, Zihao Li +6
Spiking Neural Networks (SNNs) draw inspiration from biological neurons to enable brain-like computation, demonstrating effectiveness in processing temporal information with energy…
Elucidating and Endowing the Diffusion Training Paradigm for General Image Restoration
Xin Lu, Xueyang Fu, Jie Xiao +3
While diffusion models demonstrate strong generative capabilities in image restoration (IR) tasks, their complex architectures and iterative processes limit their practical applica…
Towards Better De-raining Generalization via Rainy Characteristics Memorization and Replay
Kunyu Wang, Xueyang Fu, Chengzhi Cao +3
Current image de-raining methods primarily learn from a limited dataset, leading to inadequate performance in varied real-world rainy conditions. To tackle this, we introduce a new…
Efficient Test-time Adaptive Object Detection via Sensitivity-Guided Pruning
Kunyu Wang, Xueyang Fu, Xin Lu +4
Continual test-time adaptive object detection (CTTA-OD) aims to online adapt a source pre-trained detector to ever-changing environments during inference under continuous domain sh…
NTIRE 2025 Challenge on Event-Based Image Deblurring: Methods and Results
Lei Sun, Andrea Alfarano, Peiqi Duan +85
This paper presents an overview of NTIRE 2025 the First Challenge on Event-Based Image Deblurring, detailing the proposed methodologies and corresponding results. The primary goal…
EventMamba: Enhancing Spatio-Temporal Locality with State Space Models for Event-Based Video Reconstruction
Chengjie Ge, Xueyang Fu, Peng He +3
Leveraging its robust linear global modeling capability, Mamba has notably excelled in computer vision. Despite its success, existing Mamba-based vision models have overlooked the…
Decouple to Reconstruct: High Quality UHD Restoration via Active Feature Disentanglement and Reversible Fusion
Yidi Liu, Dong Li, Yuxin Ma +4
Ultra-high-definition (UHD) image restoration often faces computational bottlenecks and information loss due to its extremely high resolution. Existing studies based on Variational…
DemosaicFormer: Coarse-to-Fine Demosaicing Network for HybridEVS Camera
Senyan Xu, Zhijing Sun, Jiaying Zhu +3
Hybrid Event-Based Vision Sensor (HybridEVS) is a novel sensor integrating traditional frame-based and event-based sensors, offering substantial benefits for applications requiring…
Efficient Real-world Image Super-Resolution Via Adaptive Directional Gradient Convolution
Long Peng, Yang Cao, Renjing Pei +5
Real-SR endeavors to produce high-resolution images with rich details while mitigating the impact of multiple degradation factors. Although existing methods have achieved impressiv…
MIPI 2024 Challenge on Demosaic for HybridEVS Camera: Methods and Results
Yaqi Wu, Zhihao Fan, Xiaofeng Chu +46
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algor…
FourierMamba: Fourier Learning Integration with State Space Models for Image Deraining
Dong Li, Yidi Liu, Xueyang Fu +2
Image deraining aims to remove rain streaks from rainy images and restore clear backgrounds. Currently, some research that employs the Fourier transform has proved to be effective…
SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation
Hongjian Liu, Qingsong Xie, TianXiang Ye +6
The iterative sampling procedure employed by diffusion models (DMs) often leads to significant inference latency. To address this, we propose Stochastic Consistency Distillation (S…
CCM: Adding Conditional Controls to Text-to-Image Consistency Models
Jie Xiao, Kai Zhu, Han Zhang +5
Consistency Models (CMs) have showed a promise in creating visual content efficiently and with high quality. However, the way to add new conditional controls to the pretrained CMs…