{"total":176,"rows":[{"id":"2111.09881","title":"Restormer: Efficient Transformer for High-Resolution Image Restoration","created":"2021-11-18","cited_by_count":1627,"area":null},{"id":"2106.03106","title":"Uformer: A General U-Shaped Transformer for Image Restoration","created":"2021-06-06","cited_by_count":866,"area":null},{"id":"2102.02808","title":"Multi-Stage Progressive Image Restoration","created":"2021-02-04","cited_by_count":816,"area":null},{"id":"2201.02973","title":"MAXIM: Multi-Axis MLP for Image Processing","created":"2022-01-09","cited_by_count":302,"area":null},{"id":"2105.06086","title":"HINet: Half Instance Normalization Network for Image Restoration","created":"2021-05-13","cited_by_count":237,"area":null},{"id":"2205.01649","title":"Learning Enriched Features for Fast Image Restoration and Enhancement","created":"2022-04-19","cited_by_count":150,"area":null},{"id":"2204.13348","title":"Deep Generalized Unfolding Networks for Image Restoration","created":"2022-04-28","cited_by_count":121,"area":null},{"id":"2112.06409","title":"Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective","created":"2021-12-13","cited_by_count":116,"area":null},{"id":"2203.06967","title":"Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spots","created":"2022-03-14","cited_by_count":84,"area":null},{"id":"2301.03362","title":"Image Denoising: The Deep Learning Revolution and Beyond -- A Survey Paper --","created":"2023-01-09","cited_by_count":71,"area":null},{"id":"2104.10546","title":"Invertible Denoising Network: A Light Solution for Real Noise Removal","created":"2021-04-21","cited_by_count":68,"area":null},{"id":"2108.02158","title":"Physics-based Noise Modeling for Extreme Low-light Photography","created":"2021-08-04","cited_by_count":67,"area":null},{"id":"2502.20272","title":"HVI: A New Color Space for Low-light Image Enhancement","created":"2025-02-27","cited_by_count":63,"area":null},{"id":"2112.04491","title":"Improving Image Restoration by Revisiting Global Information Aggregation","created":"2021-12-08","cited_by_count":61,"area":null},{"id":"2303.13132","title":"Masked Image Training for Generalizable Deep Image Denoising","created":"2023-03-23","cited_by_count":57,"area":null},{"id":"2202.09533","title":"C2N: Practical Generative Noise Modeling for Real-World Denoising","created":"2022-02-19","cited_by_count":56,"area":null},{"id":"2109.06620","title":"Dynamic Attentive Graph Learning for Image Restoration","created":"2021-09-14","cited_by_count":48,"area":null},{"id":"2203.13009","title":"CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Image","created":"2022-03-24","cited_by_count":45,"area":null},{"id":"2204.07756","title":"Visual Attention Methods in Deep Learning: An In-Depth Survey","created":"2022-04-16","cited_by_count":37,"area":null},{"id":"2303.06440","title":"Xformer: Hybrid X-Shaped Transformer for Image Denoising","created":"2023-03-11","cited_by_count":37,"area":null},{"id":"2304.00534","title":"LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising","created":"2023-04-02","cited_by_count":37,"area":null},{"id":"2312.17334","title":"Improving Image Restoration through Removing Degradations in Textual Representations","created":"2023-12-28","cited_by_count":36,"area":null},{"id":"2303.02881","title":"KBNet: Kernel Basis Network for Image Restoration","created":"2023-03-06","cited_by_count":33,"area":null},{"id":"2303.14934","title":"Spatially Adaptive Self-Supervised Learning for Real-World Image Denoising","created":"2023-03-27","cited_by_count":33,"area":null},{"id":"2307.16825","title":"Random Sub-Samples Generation for Self-Supervised Real Image Denoising","created":"2023-07-31","cited_by_count":31,"area":null},{"id":"2304.01598","title":"MM-BSN: Self-Supervised Image Denoising for Real-World with Multi-Mask based on Blind-Spot Network","created":"2023-04-04","cited_by_count":30,"area":null},{"id":"2204.02844","title":"Learning to Generate Realistic Noisy Images via Pixel-level Noise-aware Adversarial Training","created":"2022-04-06","cited_by_count":29,"area":null},{"id":"2308.06776","title":"Unsupervised Image Denoising in Real-World Scenarios via Self-Collaboration Parallel Generative Adversarial Branches","created":"2023-08-13","cited_by_count":29,"area":null},{"id":"2211.12051","title":"Adaptive Dynamic Filtering Network for Image Denoising","created":"2022-11-22","cited_by_count":28,"area":null},{"id":"2302.02398","title":"Diffusion Model for Generative Image Denoising","created":"2023-02-05","cited_by_count":28,"area":"diffusion"},{"id":"2506.16960","title":"Visual-Instructed Degradation Diffusion for All-in-One Image Restoration","created":"2025-06-20","cited_by_count":26,"area":null},{"id":"2204.12347","title":"Restricted Black-box Adversarial Attack Against DeepFake Face Swapping","created":"2022-04-26","cited_by_count":25,"area":null},{"id":"2207.01074","title":"Variational Deep Image Restoration","created":"2022-07-03","cited_by_count":24,"area":null},{"id":"2404.11778","title":"CU-Mamba: Selective State Space Models with Channel Learning for Image Restoration","created":"2024-04-17","cited_by_count":24,"area":"ssm"},{"id":"2101.09870","title":"Joint Denoising and Demosaicking with Green Channel Prior for Real-world Burst Images","created":"2021-01-25","cited_by_count":18,"area":null},{"id":"2204.10090","title":"Learn from Unpaired Data for Image Restoration: A Variational Bayes Approach","created":"2022-04-21","cited_by_count":18,"area":null},{"id":"2210.13552","title":"Perceptual Image Enhancement for Smartphone Real-Time Applications","created":"2022-10-24","cited_by_count":18,"area":null},{"id":"2203.04313","title":"Multi-Scale Adaptive Network for Single Image Denoising","created":"2022-03-08","cited_by_count":17,"area":null},{"id":"2303.06859","title":"Learning Distortion Invariant Representation for Image Restoration from A Causality Perspective","created":"2023-03-13","cited_by_count":17,"area":null},{"id":"2303.16783","title":"Exploring Efficient Asymmetric Blind-Spots for Self-Supervised Denoising in Real-World Scenarios","created":"2023-03-29","cited_by_count":17,"area":null},{"id":"2307.09039","title":"PottsMGNet: A Mathematical Explanation of Encoder-Decoder Based Neural Networks","created":"2023-07-18","cited_by_count":17,"area":null},{"id":"2308.00247","title":"Unleashing the Power of Self-Supervised Image Denoising: A Comprehensive Review","created":"2023-08-01","cited_by_count":17,"area":null},{"id":"2103.05961","title":"COLA-Net: Collaborative Attention Network for Image Restoration","created":"2021-03-10","cited_by_count":16,"area":null},{"id":"2306.05390","title":"HQ-50K: A Large-scale, High-quality Dataset for Image Restoration","created":"2023-06-08","cited_by_count":16,"area":null},{"id":"2207.03294","title":"D2HNet: Joint Denoising and Deblurring with Hierarchical Network for Robust Night Image Restoration","created":"2022-07-07","cited_by_count":14,"area":null},{"id":"2208.12044","title":"Fed-FSNet: Mitigating Non-I.I.D. Federated Learning via Fuzzy Synthesizing Network","created":"2022-08-21","cited_by_count":14,"area":null},{"id":"2302.09554","title":"Mixed Hierarchy Network for Image Restoration","created":"2023-02-19","cited_by_count":14,"area":null},{"id":"2201.04397","title":"Towards Adversarially Robust Deep Image Denoising","created":"2022-01-12","cited_by_count":13,"area":null},{"id":"2304.01627","title":"Self-Supervised Image Denoising for Real-World Images with Context-aware Transformer","created":"2023-04-04","cited_by_count":13,"area":null},{"id":"2209.11448","title":"Rethinking Performance Gains in Image Dehazing Networks","created":"2022-09-23","cited_by_count":12,"area":null},{"id":"2304.09507","title":"Self-supervised Image Denoising with Downsampled Invariance Loss and Conditional Blind-Spot Network","created":"2023-04-19","cited_by_count":12,"area":null},{"id":"2203.10247","title":"HIPA: Hierarchical Patch Transformer for Single Image Super Resolution","created":"2022-03-19","cited_by_count":11,"area":null},{"id":"2304.06274","title":"EWT: Efficient Wavelet-Transformer for Single Image Denoising","created":"2023-04-13","cited_by_count":11,"area":null},{"id":"2101.07017","title":"Deep Universal Blind Image Denoising","created":"2021-01-18","cited_by_count":10,"area":null},{"id":"2103.10234","title":"Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser","created":"2021-03-18","cited_by_count":10,"area":null},{"id":"2108.00620","title":"Investigating Attention Mechanism in 3D Point Cloud Object Detection","created":"2021-08-02","cited_by_count":10,"area":null},{"id":"2206.02609","title":"Real-World Image Super-Resolution by Exclusionary Dual-Learning","created":"2022-06-06","cited_by_count":10,"area":null},{"id":"2206.03697","title":"Blind Face Restoration: Benchmark Datasets and a Baseline Model","created":"2022-06-08","cited_by_count":10,"area":null},{"id":"2405.01725","title":"Development of Skip Connection in Deep Neural Networks for Computer Vision and Medical Image Analysis: A Survey","created":"2024-05-02","cited_by_count":10,"area":null},{"id":"2412.10651","title":"LAN: Learning to Adapt Noise for Image Denoising","created":"2024-12-14","cited_by_count":10,"area":null},{"id":"2506.22246","title":"EAMamba: Efficient All-Around Vision State Space Model for Image Restoration","created":"2025-06-27","cited_by_count":10,"area":"ssm"},{"id":"2110.08940","title":"Dynamic Slimmable Denoising Network","created":"2021-10-17","cited_by_count":9,"area":null},{"id":"2111.00361","title":"Functional Neural Networks for Parametric Image Restoration Problems","created":"2021-10-30","cited_by_count":9,"area":null},{"id":"2303.16425","title":"Real-time Controllable Denoising for Image and Video","created":"2023-03-29","cited_by_count":9,"area":null},{"id":"2504.13112","title":"Hadamard product in deep learning: Introduction, Advances and Challenges","created":"2025-04-17","cited_by_count":9,"area":null},{"id":"2201.01014","title":"Local Motion and Contrast Priors Driven Deep Network for Infrared Small Target Super-Resolution","created":"2022-01-04","cited_by_count":8,"area":null},{"id":"2203.11754","title":"Exploring and Evaluating Image Restoration Potential in Dynamic Scenes","created":"2022-03-22","cited_by_count":8,"area":null},{"id":"2303.17316","title":"Masked Autoencoders as Image Processors","created":"2023-03-30","cited_by_count":8,"area":null},{"id":"2407.03535","title":"BVI-RLV: A Fully Registered Dataset for Low-Light Video Enhancement","created":"2024-07-03","cited_by_count":8,"area":null},{"id":"2407.19789","title":"Interpreting Low-level Vision Models with Causal Effect Maps","created":"2024-07-29","cited_by_count":8,"area":null},{"id":"2105.04746","title":"Disentangling Noise from Images: A Flow-Based Image Denoising Neural Network","created":"2021-05-11","cited_by_count":7,"area":null},{"id":"2105.09437","title":"End-to-End Unsupervised Document Image Blind Denoising","created":"2021-05-19","cited_by_count":7,"area":null},{"id":"2304.08990","title":"A Comparison of Image Denoising Methods","created":"2023-04-18","cited_by_count":7,"area":null},{"id":"2402.11957","title":"Event-Based Motion Magnification","created":"2024-02-19","cited_by_count":7,"area":null},{"id":"2404.00633","title":"IPT-V2: Efficient Image Processing Transformer using Hierarchical Attentions","created":"2024-03-31","cited_by_count":7,"area":null},{"id":"2408.09241","title":"Re-boosting Self-Collaboration Parallel Prompt GAN for Unsupervised Image Restoration","created":"2024-08-17","cited_by_count":7,"area":null},{"id":"2106.06927","title":"Inverting Adversarially Robust Networks for Image Synthesis","created":"2021-06-13","cited_by_count":6,"area":null},{"id":"2201.00392","title":"Fast and High-Quality Image Denoising via Malleable Convolutions","created":"2022-01-02","cited_by_count":6,"area":null},{"id":"2205.06944","title":"Dense residual Transformer for image denoising","created":"2022-05-14","cited_by_count":6,"area":null},{"id":"2302.13598","title":"Spatial-Frequency Attention for Image Denoising","created":"2023-02-27","cited_by_count":6,"area":null},{"id":"2305.04269","title":"Dual Residual Attention Network for Image Denoising","created":"2023-05-07","cited_by_count":6,"area":null},{"id":"2309.08826","title":"Dual-Camera Joint Deblurring-Denoising","created":"2023-09-16","cited_by_count":6,"area":null},{"id":"2310.10408","title":"A cross Transformer for image denoising","created":"2023-10-16","cited_by_count":6,"area":null},{"id":"2407.06514","title":"Asymmetric Mask Scheme for Self-Supervised Real Image Denoising","created":"2024-07-09","cited_by_count":6,"area":null},{"id":"2505.19618","title":"Rotation-Equivariant Self-Supervised Method in Image Denoising","created":"2025-05-26","cited_by_count":6,"area":null},{"id":"2009.14563","title":"Restoring Spatially-Heterogeneous Distortions using Mixture of Experts Network","created":"2020-09-30","cited_by_count":5,"area":"moe"},{"id":"2201.10084","title":"Revisiting L1 Loss in Super-Resolution: A Probabilistic View and Beyond","created":"2022-01-25","cited_by_count":5,"area":null},{"id":"2203.01645","title":"Selective Residual M-Net for Real Image Denoising","created":"2022-03-03","cited_by_count":5,"area":null},{"id":"2208.11803","title":"Learning Task-Oriented Flows to Mutually Guide Feature Alignment in Synthesized and Real Video Denoising","created":"2022-08-25","cited_by_count":5,"area":null},{"id":"2305.14022","title":"Realistic Noise Synthesis with Diffusion Models","created":"2023-05-23","cited_by_count":5,"area":"diffusion"},{"id":"2407.05709","title":"Heterogeneous window transformer for image denoising","created":"2024-07-08","cited_by_count":5,"area":null},{"id":"2412.16645","title":"Complementary Advantages: Exploiting Cross-Field Frequency Correlation for NIR-Assisted Image Denoising","created":"2024-12-21","cited_by_count":5,"area":null},{"id":"2502.06432","title":"Prompt-SID: Learning Structural Representation Prompt via Latent Diffusion for Single-Image Denoising","created":"2025-02-10","cited_by_count":5,"area":"diffusion"},{"id":"2604.11468","title":"Beyond Model Design: Data-Centric Training and Self-Ensemble for Gaussian Color Image Denoising","created":"2026-04-13","cited_by_count":5,"area":null},{"id":"2101.04631","title":"Deep Gaussian Denoiser Epistemic Uncertainty and Decoupled Dual-Attention Fusion","created":"2021-01-12","cited_by_count":4,"area":null},{"id":"2206.03691","title":"Robust Deep Ensemble Method for Real-world Image Denoising","created":"2022-06-08","cited_by_count":4,"area":null},{"id":"2301.13554","title":"NoiseTransfer: Image Noise Generation with Contrastive Embeddings","created":"2023-01-31","cited_by_count":4,"area":null},{"id":"2304.01620","title":"Image Blind Denoising Using Dual Convolutional Neural Network with Skip Connection","created":"2023-04-04","cited_by_count":4,"area":null},{"id":"2402.01970","title":"BVI-Lowlight: Fully Registered Benchmark Dataset for Low-Light Video Enhancement","created":"2024-02-03","cited_by_count":4,"area":null},{"id":"2410.04434","title":"A Mathematical Explanation of UNet","created":"2024-10-06","cited_by_count":4,"area":null}],"next_cursor":"100"}