{"total":175,"rows":[{"id":"2107.10833","title":"Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data","created":"2021-07-22","cited_by_count":970,"area":null},{"id":"2103.14006","title":"Designing a Practical Degradation Model for Deep Blind Image Super-Resolution","created":"2021-03-25","cited_by_count":529,"area":null},{"id":"2401.13627","title":"Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild","created":"2024-01-24","cited_by_count":286,"area":null},{"id":"2203.06026","title":"The Role of ImageNet Classes in Fr\\'echet Inception Distance","created":"2022-03-11","cited_by_count":213,"area":null},{"id":"2104.00416","title":"Unsupervised Degradation Representation Learning for Blind Super-Resolution","created":"2021-04-01","cited_by_count":177,"area":null},{"id":"2103.10427","title":"The Low-Rank Simplicity Bias in Deep Networks","created":"2021-03-18","cited_by_count":154,"area":null},{"id":"2107.03055","title":"Blind Image Super-Resolution: A Survey and Beyond","created":"2021-07-07","cited_by_count":93,"area":null},{"id":"2103.15977","title":"Flow-based Kernel Prior with Application to Blind Super-Resolution","created":"2021-03-29","cited_by_count":74,"area":null},{"id":"2103.02368","title":"Real-World Single Image Super-Resolution: A Brief Review","created":"2021-03-03","cited_by_count":65,"area":null},{"id":"2203.16262","title":"How Does SimSiam Avoid Collapse Without Negative Samples? A Unified Understanding with Self-supervised Contrastive Learning","created":"2022-03-30","cited_by_count":65,"area":null},{"id":"2108.05302","title":"Mutual Affine Network for Spatially Variant Kernel Estimation in Blind Image Super-Resolution","created":"2021-08-11","cited_by_count":52,"area":null},{"id":"2202.07508","title":"Deep Constrained Least Squares for Blind Image Super-Resolution","created":"2022-02-15","cited_by_count":47,"area":null},{"id":"2110.10394","title":"Deep Learning for HDR Imaging: State-of-the-Art and Future Trends","created":"2021-10-20","cited_by_count":45,"area":null},{"id":"2112.12089","title":"Reflash Dropout in Image Super-Resolution","created":"2021-12-22","cited_by_count":41,"area":null},{"id":"2309.00287","title":"Fast Diffusion EM: a diffusion model for blind inverse problems with application to deconvolution","created":"2023-09-01","cited_by_count":36,"area":"diffusion"},{"id":"2108.10290","title":"Cross-Quality LFW: A Database for Analyzing Cross-Resolution Image Face Recognition in Unconstrained Environments","created":"2021-08-23","cited_by_count":34,"area":null},{"id":"2205.05065","title":"MM-RealSR: Metric Learning based Interactive Modulation for Real-World Super-Resolution","created":"2022-05-10","cited_by_count":33,"area":null},{"id":"2107.00708","title":"Blind Image Super-Resolution via Contrastive Representation Learning","created":"2021-07-01","cited_by_count":32,"area":null},{"id":"2104.09556","title":"Removing Diffraction Image Artifacts in Under-Display Camera via Dynamic Skip Connection Network","created":"2021-04-19","cited_by_count":31,"area":null},{"id":"2101.05796","title":"DeFlow: Learning Complex Image Degradations from Unpaired Data with Conditional Flows","created":"2021-01-14","cited_by_count":30,"area":null},{"id":"2203.11509","title":"Unsupervised Deraining: Where Contrastive Learning Meets Self-similarity","created":"2022-03-22","cited_by_count":30,"area":null},{"id":"2107.00986","title":"Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel","created":"2021-07-02","cited_by_count":27,"area":null},{"id":"2203.04962","title":"Learning the Degradation Distribution for Blind Image Super-Resolution","created":"2022-03-09","cited_by_count":27,"area":null},{"id":"2108.01070","title":"Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution","created":"2021-08-02","cited_by_count":26,"area":null},{"id":"2312.08886","title":"Diffusion-based Blind Text Image Super-Resolution","created":"2023-12-13","cited_by_count":25,"area":"diffusion"},{"id":"2207.01074","title":"Variational Deep Image Restoration","created":"2022-07-03","cited_by_count":24,"area":null},{"id":"2303.14726","title":"Learning Generative Structure Prior for Blind Text Image Super-resolution","created":"2023-03-26","cited_by_count":24,"area":null},{"id":"2206.07038","title":"AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos","created":"2022-06-14","cited_by_count":23,"area":null},{"id":"2311.14282","title":"Image Super-Resolution with Text Prompt Diffusion","created":"2023-11-24","cited_by_count":23,"area":null},{"id":"2205.04910","title":"A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds","created":"2022-05-10","cited_by_count":22,"area":null},{"id":"2302.12831","title":"CDPMSR: Conditional Diffusion Probabilistic Models for Single Image Super-Resolution","created":"2023-02-14","cited_by_count":21,"area":"diffusion"},{"id":"2305.18107","title":"Crafting Training Degradation Distribution for the Accuracy-Generalization Trade-off in Real-World Super-Resolution","created":"2023-05-29","cited_by_count":21,"area":null},{"id":"2108.00406","title":"Discovering Distinctive \"Semantics\" in Super-Resolution Networks","created":"2021-08-01","cited_by_count":20,"area":null},{"id":"2203.01325","title":"Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed Observations","created":"2022-03-02","cited_by_count":20,"area":null},{"id":"2208.09885","title":"HST: Hierarchical Swin Transformer for Compressed Image Super-resolution","created":"2022-08-21","cited_by_count":20,"area":null},{"id":"2303.13069","title":"Human Guided Ground-truth Generation for Realistic Image Super-resolution","created":"2023-03-23","cited_by_count":20,"area":null},{"id":"2306.01154","title":"The Law of Parsimony in Gradient Descent for Learning Deep Linear Networks","created":"2023-06-01","cited_by_count":20,"area":null},{"id":"2304.07018","title":"DIPNet: Efficiency Distillation and Iterative Pruning for Image Super-Resolution","created":"2023-04-14","cited_by_count":19,"area":null},{"id":"2403.02601","title":"Low-Res Leads the Way: Improving Generalization for Super-Resolution by Self-Supervised Learning","created":"2024-03-05","cited_by_count":19,"area":null},{"id":"2105.12409","title":"Permutation invariance and uncertainty in multitemporal image super-resolution","created":"2021-05-26","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":"2205.07019","title":"Evaluating the Generalization Ability of Super-Resolution Networks","created":"2022-05-14","cited_by_count":18,"area":null},{"id":"2209.10305","title":"KXNet: A Model-Driven Deep Neural Network for Blind Super-Resolution","created":"2022-09-21","cited_by_count":18,"area":null},{"id":"2307.00781","title":"ACDMSR: Accelerated Conditional Diffusion Models for Single Image Super-Resolution","created":"2023-07-03","cited_by_count":18,"area":"diffusion"},{"id":"2310.19011","title":"Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction","created":"2023-10-29","cited_by_count":18,"area":null},{"id":"2105.06878","title":"End-to-end Alternating Optimization for Blind Super Resolution","created":"2021-05-14","cited_by_count":17,"area":null},{"id":"2201.07422","title":"Self-Supervised Deep Blind Video Super-Resolution","created":"2022-01-19","cited_by_count":15,"area":null},{"id":"2210.00752","title":"From Face to Natural Image: Learning Real Degradation for Blind Image Super-Resolution","created":"2022-10-03","cited_by_count":15,"area":null},{"id":"2307.14659","title":"LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image Enhancement","created":"2023-07-27","cited_by_count":15,"area":"diffusion"},{"id":"2404.15620","title":"A Dynamic Kernel Prior Model for Unsupervised Blind Image Super-Resolution","created":"2024-04-24","cited_by_count":15,"area":"diffusion"},{"id":"2109.03444","title":"Toward Real-World Super-Resolution via Adaptive Downsampling Models","created":"2021-09-08","cited_by_count":14,"area":null},{"id":"2310.04180","title":"Degradation-Aware Self-Attention Based Transformer for Blind Image Super-Resolution","created":"2023-10-06","cited_by_count":14,"area":null},{"id":"2106.07140","title":"SinIR: Efficient General Image Manipulation with Single Image Reconstruction","created":"2021-06-14","cited_by_count":13,"area":null},{"id":"2207.07929","title":"Towards Lightweight Super-Resolution with Dual Regression Learning","created":"2022-07-16","cited_by_count":13,"area":null},{"id":"2305.02660","title":"Expanding Synthetic Real-World Degradations for Blind Video Super Resolution","created":"2023-05-04","cited_by_count":12,"area":null},{"id":"2309.03020","title":"SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution","created":"2023-09-06","cited_by_count":12,"area":null},{"id":"2405.07012","title":"Incorporating Degradation Estimation in Light Field Spatial Super-Resolution","created":"2024-05-11","cited_by_count":12,"area":null},{"id":"2102.03113","title":"Real-World Super-Resolution of Face-Images from Surveillance Cameras","created":"2021-02-05","cited_by_count":11,"area":null},{"id":"2111.10800","title":"FreqNet: A Frequency-domain Image Super-Resolution Network with Dicrete Cosine Transform","created":"2021-11-21","cited_by_count":11,"area":null},{"id":"2204.00623","title":"Bayesian Image Super-Resolution with Deep Modeling of Image Statistics","created":"2022-03-31","cited_by_count":11,"area":null},{"id":"2204.13620","title":"Generative Adversarial Networks for Image Super-Resolution: A Survey","created":"2022-04-28","cited_by_count":11,"area":null},{"id":"2207.13963","title":"Meta-Learning based Degradation Representation for Blind Super-Resolution","created":"2022-07-28","cited_by_count":11,"area":null},{"id":"2303.06994","title":"Synthesizing Realistic Image Restoration Training Pairs: A Diffusion Approach","created":"2023-03-13","cited_by_count":11,"area":"diffusion"},{"id":"2204.10109","title":"Deep Model-Based Super-Resolution with Non-uniform Blur","created":"2022-04-21","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":"2304.10536","title":"Learning Sparse and Low-Rank Priors for Image Recovery via Iterative Reweighted Least Squares Minimization","created":"2023-04-20","cited_by_count":10,"area":null},{"id":"2404.08412","title":"PiRD: Physics-informed Residual Diffusion for Flow Field Reconstruction","created":"2024-04-12","cited_by_count":10,"area":"diffusion"},{"id":"2106.03727","title":"Deep Neural Network-based Enhancement for Image and Video Streaming Systems: A Survey and Future Directions","created":"2021-06-07","cited_by_count":9,"area":null},{"id":"2108.11505","title":"Generalized Real-World Super-Resolution through Adversarial Robustness","created":"2021-08-25","cited_by_count":9,"area":null},{"id":"2305.18547","title":"Learning from Multi-Perception Features for Real-Word Image Super-resolution","created":"2023-05-26","cited_by_count":9,"area":null},{"id":"2312.07425","title":"Deep Internal Learning: Deep Learning from a Single Input","created":"2023-12-12","cited_by_count":9,"area":null},{"id":"2406.18516","title":"Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration","created":"2024-06-26","cited_by_count":9,"area":"diffusion"},{"id":"2103.13389","title":"Generating Novel Scene Compositions from Single Images and Videos","created":"2021-03-24","cited_by_count":8,"area":null},{"id":"2104.09435","title":"Deep learning enables reference-free isotropic super-resolution for volumetric fluorescence microscopy","created":"2021-04-19","cited_by_count":8,"area":null},{"id":"2207.12767","title":"Criteria Comparative Learning for Real-scene Image Super-Resolution","created":"2022-07-26","cited_by_count":8,"area":null},{"id":"2208.11313","title":"RZSR: Reference-based Zero-Shot Super-Resolution with Depth Guided Self-Exemplars","created":"2022-08-24","cited_by_count":8,"area":null},{"id":"2208.13436","title":"Joint Learning Content and Degradation Aware Feature for Blind Super-Resolution","created":"2022-08-29","cited_by_count":8,"area":null},{"id":"2308.08816","title":"End-to-end Alternating Optimization for Real-World Blind Super Resolution","created":"2023-08-17","cited_by_count":8,"area":null},{"id":"2405.07648","title":"CDFormer:When Degradation Prediction Embraces Diffusion Model for Blind Image Super-Resolution","created":"2024-05-13","cited_by_count":8,"area":"diffusion"},{"id":"2411.18662","title":"HoliSDiP: Image Super-Resolution via Holistic Semantics and Diffusion Prior","created":"2024-11-27","cited_by_count":8,"area":"diffusion"},{"id":"2104.03926","title":"Conditional Hyper-Network for Blind Super-Resolution with Multiple Degradations","created":"2021-04-08","cited_by_count":7,"area":null},{"id":"2109.14406","title":"Neural Knitworks: Patched Neural Implicit Representation Networks","created":"2021-09-29","cited_by_count":7,"area":null},{"id":"2110.12151","title":"Spectrum-to-Kernel Translation for Accurate Blind Image Super-Resolution","created":"2021-10-23","cited_by_count":7,"area":null},{"id":"2203.05568","title":"Unfolded Deep Kernel Estimation for Blind Image Super-resolution","created":"2022-03-10","cited_by_count":7,"area":null},{"id":"2207.00943","title":"Degradation-Guided Meta-Restoration Network for Blind Super-Resolution","created":"2022-07-03","cited_by_count":7,"area":null},{"id":"2211.00837","title":"Unsupervised Deraining: Where Asymmetric Contrastive Learning Meets Self-similarity","created":"2022-11-02","cited_by_count":7,"area":null},{"id":"2304.03542","title":"Better \"CMOS\" Produces Clearer Images: Learning Space-Variant Blur Estimation for Blind Image Super-Resolution","created":"2023-04-07","cited_by_count":7,"area":null},{"id":"2305.12170","title":"Dual-Diffusion: Dual Conditional Denoising Diffusion Probabilistic Models for Blind Super-Resolution Reconstruction in RSIs","created":"2023-05-20","cited_by_count":7,"area":"diffusion"},{"id":"2310.04964","title":"Learning Many-to-Many Mapping for Unpaired Real-World Image Super-resolution and Downscaling","created":"2023-10-08","cited_by_count":7,"area":null},{"id":"2406.08896","title":"Blind Super-Resolution via Meta-learning and Markov Chain Monte Carlo Simulation","created":"2024-06-13","cited_by_count":7,"area":null},{"id":"2103.00430","title":"Training Generative Adversarial Networks in One Stage","created":"2021-02-28","cited_by_count":6,"area":null},{"id":"2208.03062","title":"Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection","created":"2022-08-05","cited_by_count":6,"area":null},{"id":"2212.01624","title":"Learning Detail-Structure Alternative Optimization for Blind Super-Resolution","created":"2022-12-03","cited_by_count":6,"area":null},{"id":"2401.07139","title":"Deep Blind Super-Resolution for Satellite Video","created":"2024-01-13","cited_by_count":6,"area":null},{"id":"2112.07315","title":"Kernel-aware Burst Blind Super-Resolution","created":"2021-12-14","cited_by_count":5,"area":null},{"id":"2211.14040","title":"Real-Time Under-Display Cameras Image Restoration and HDR on Mobile Devices","created":"2022-11-25","cited_by_count":5,"area":null},{"id":"2312.07835","title":"Video Dynamics Prior: An Internal Learning Approach for Robust Video Enhancements","created":"2023-12-13","cited_by_count":5,"area":null},{"id":"2403.10211","title":"BlindDiff: Empowering Degradation Modelling in Diffusion Models for Blind Image Super-Resolution","created":"2024-03-15","cited_by_count":5,"area":"diffusion"},{"id":"2406.13652","title":"Stability and Generalizability in SDE Diffusion Models with Measure-Preserving Dynamics","created":"2024-06-19","cited_by_count":5,"area":"diffusion"},{"id":"2506.14605","title":"Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching","created":"2025-06-17","cited_by_count":5,"area":null}],"next_cursor":"100"}