{"total":1004,"rows":[{"id":"2108.10257","title":"SwinIR: Image Restoration Using Swin Transformer","created":"2021-08-23","cited_by_count":1887,"area":null},{"id":"2104.07636","title":"Image Super-Resolution via Iterative Refinement","created":"2021-04-15","cited_by_count":1511,"area":null},{"id":"2101.01169","title":"Transformers in Vision: A Survey","created":"2021-01-04","cited_by_count":1013,"area":null},{"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":"2102.02808","title":"Multi-Stage Progressive Image Restoration","created":"2021-02-04","cited_by_count":816,"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":"2204.08958","title":"MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment","created":"2022-04-19","cited_by_count":522,"area":null},{"id":"2303.05511","title":"Scaling up GANs for Text-to-Image Synthesis","created":"2023-03-09","cited_by_count":492,"area":null},{"id":"2205.04437","title":"Activating More Pixels in Image Super-Resolution Transformer","created":"2022-05-09","cited_by_count":438,"area":null},{"id":"2101.04061","title":"Towards Real-World Blind Face Restoration with Generative Facial Prior","created":"2021-01-11","cited_by_count":349,"area":null},{"id":"2201.02973","title":"MAXIM: Multi-Axis MLP for Image Processing","created":"2022-01-09","cited_by_count":302,"area":null},{"id":"2301.09515","title":"StyleGAN-T: Unlocking the Power of GANs for Fast Large-Scale Text-to-Image Synthesis","created":"2023-01-23","cited_by_count":212,"area":null},{"id":"2105.07581","title":"Vision Transformers are Robust Learners","created":"2021-05-17","cited_by_count":207,"area":null},{"id":"2105.14951","title":"SNIPS: Solving Noisy Inverse Problems Stochastically","created":"2021-05-31","cited_by_count":191,"area":null},{"id":"2109.05923","title":"Low-Light Image Enhancement with Normalizing Flow","created":"2021-09-13","cited_by_count":185,"area":null},{"id":"2205.03409","title":"VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolution","created":"2022-05-06","cited_by_count":176,"area":null},{"id":"2203.06697","title":"Efficient Long-Range Attention Network for Image Super-resolution","created":"2022-03-13","cited_by_count":151,"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":"2104.10729","title":"Low-Light Image and Video Enhancement Using Deep Learning: A Survey","created":"2021-04-21","cited_by_count":148,"area":null},{"id":"2303.00748","title":"Efficient and Explicit Modelling of Image Hierarchies for Image Restoration","created":"2023-03-01","cited_by_count":145,"area":null},{"id":"2401.16468","title":"InstructIR: High-Quality Image Restoration Following Human Instructions","created":"2024-01-29","cited_by_count":140,"area":null},{"id":"2111.12704","title":"Investigating Tradeoffs in Real-World Video Super-Resolution","created":"2021-11-24","cited_by_count":134,"area":null},{"id":"2203.09195","title":"Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution","created":"2022-03-17","cited_by_count":114,"area":null},{"id":"2202.03373","title":"LEDNet: Joint Low-light Enhancement and Deblurring in the Dark","created":"2022-02-07","cited_by_count":96,"area":null},{"id":"2203.14216","title":"Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution","created":"2022-03-27","cited_by_count":96,"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":"2403.11423","title":"VmambaIR: Visual State Space Model for Image Restoration","created":"2024-03-18","cited_by_count":90,"area":null},{"id":"2105.10422","title":"LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond","created":"2021-05-21","cited_by_count":88,"area":null},{"id":"2303.11717","title":"A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?","created":"2023-03-21","cited_by_count":84,"area":null},{"id":"2101.10997","title":"Deep Burst Super-Resolution","created":"2021-01-26","cited_by_count":83,"area":null},{"id":"2103.14756","title":"Equivariant Imaging: Learning Beyond the Range Space","created":"2021-03-26","cited_by_count":83,"area":null},{"id":"2103.11298","title":"Deep Dense Multi-scale Network for Snow Removal Using Semantic and Geometric Priors","created":"2021-03-21","cited_by_count":82,"area":null},{"id":"2103.04039","title":"ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic","created":"2021-03-06","cited_by_count":81,"area":null},{"id":"2106.02299","title":"MASA-SR: Matching Acceleration and Spatial Adaptation for Reference-Based Image Super-Resolution","created":"2021-06-04","cited_by_count":80,"area":null},{"id":"2203.03121","title":"Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer","created":"2022-03-07","cited_by_count":78,"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":"2309.14494","title":"Free-Bloom: Zero-Shot Text-to-Video Generator with LLM Director and LDM Animator","created":"2023-09-25","cited_by_count":74,"area":null},{"id":"2106.00783","title":"Fourier Space Losses for Efficient Perceptual Image Super-Resolution","created":"2021-06-01","cited_by_count":73,"area":null},{"id":"2108.05301","title":"Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling","created":"2021-08-11","cited_by_count":73,"area":null},{"id":"2206.07255","title":"GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifolds","created":"2022-06-15","cited_by_count":73,"area":null},{"id":"2209.11345","title":"Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration","created":"2022-09-22","cited_by_count":73,"area":null},{"id":"2204.07156","title":"Any-resolution Training for High-resolution Image Synthesis","created":"2022-04-14","cited_by_count":72,"area":null},{"id":"2212.04362","title":"CiaoSR: Continuous Implicit Attention-in-Attention Network for Arbitrary-Scale Image Super-Resolution","created":"2022-12-08","cited_by_count":70,"area":null},{"id":"2106.01863","title":"Robust Reference-based Super-Resolution via C2-Matching","created":"2021-06-03","cited_by_count":69,"area":null},{"id":"2309.05239","title":"HAT: Hybrid Attention Transformer for Image Restoration","created":"2023-09-11","cited_by_count":66,"area":null},{"id":"2311.16512","title":"CoSeR: Bridging Image and Language for Cognitive Super-Resolution","created":"2023-11-27","cited_by_count":66,"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":"2110.03680","title":"Burst Image Restoration and Enhancement","created":"2021-10-07","cited_by_count":64,"area":null},{"id":"2112.10175","title":"On Efficient Transformer-Based Image Pre-training for Low-Level Vision","created":"2021-12-19","cited_by_count":64,"area":null},{"id":"2305.17863","title":"GridFormer: Residual Dense Transformer with Grid Structure for Image Restoration in Adverse Weather Conditions","created":"2023-05-29","cited_by_count":62,"area":null},{"id":"2204.11425","title":"BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix","created":"2022-04-25","cited_by_count":61,"area":null},{"id":"2106.07873","title":"Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images","created":"2021-06-15","cited_by_count":58,"area":null},{"id":"2204.10485","title":"Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network","created":"2022-04-22","cited_by_count":57,"area":null},{"id":"2406.07255","title":"Towards Realistic Data Generation for Real-World Super-Resolution","created":"2024-06-11","cited_by_count":56,"area":null},{"id":"2201.03299","title":"Avoiding Overfitting: A Survey on Regularization Methods for Convolutional Neural Networks","created":"2022-01-10","cited_by_count":55,"area":null},{"id":"2104.14730","title":"Perceptual Image Quality Assessment with Transformers","created":"2021-04-30","cited_by_count":54,"area":null},{"id":"2107.02555","title":"A Theory of the Distortion-Perception Tradeoff in Wasserstein Space","created":"2021-07-06","cited_by_count":52,"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":"2303.16513","title":"Cascaded Local Implicit Transformer for Arbitrary-Scale Super-Resolution","created":"2023-03-29","cited_by_count":52,"area":null},{"id":"2207.11938","title":"Reference-based Image Super-Resolution with Deformable Attention Transformer","created":"2022-07-25","cited_by_count":51,"area":null},{"id":"2104.14854","title":"NTIRE 2021 Challenge on Image Deblurring","created":"2021-04-30","cited_by_count":50,"area":null},{"id":"2308.12770","title":"WavMark: Watermarking for Audio Generation","created":"2023-08-24","cited_by_count":50,"area":null},{"id":"2503.06617","title":"Pixel to Gaussian: Ultra-Fast Continuous Super-Resolution with 2D Gaussian Modeling","created":"2025-03-09","cited_by_count":48,"area":null},{"id":"2110.11728","title":"BlendGAN: Implicitly GAN Blending for Arbitrary Stylized Face Generation","created":"2021-10-22","cited_by_count":47,"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":"2310.12848","title":"Neural Degradation Representation Learning for All-In-One Image Restoration","created":"2023-10-19","cited_by_count":46,"area":null},{"id":"2103.09950","title":"Learning to Resize Images for Computer Vision Tasks","created":"2021-03-17","cited_by_count":45,"area":null},{"id":"2203.15190","title":"3D Shape Reconstruction from 2D Images with Disentangled Attribute Flow","created":"2022-03-29","cited_by_count":45,"area":null},{"id":"2205.15175","title":"ShuffleMixer: An Efficient ConvNet for Image Super-Resolution","created":"2022-05-30","cited_by_count":45,"area":null},{"id":"2108.08119","title":"Learning RAW-to-sRGB Mappings with Inaccurately Aligned Supervision","created":"2021-08-18","cited_by_count":43,"area":null},{"id":"2202.10603","title":"Disentangling Light Fields for Super-Resolution and Disparity Estimation","created":"2022-02-22","cited_by_count":42,"area":null},{"id":"2405.13570","title":"MetaEarth: A Generative Foundation Model for Global-Scale Remote Sensing Image Generation","created":"2024-05-22","cited_by_count":42,"area":null},{"id":"2112.12089","title":"Reflash Dropout in Image Super-Resolution","created":"2021-12-22","cited_by_count":41,"area":null},{"id":"2206.11695","title":"NTIRE 2022 Challenge on Perceptual Image Quality Assessment","created":"2022-06-23","cited_by_count":41,"area":null},{"id":"2307.02457","title":"DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models","created":"2023-07-05","cited_by_count":41,"area":null},{"id":"2205.05675","title":"NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results","created":"2022-05-11","cited_by_count":40,"area":null},{"id":"2210.08160","title":"Learning Dual Memory Dictionaries for Blind Face Restoration","created":"2022-10-15","cited_by_count":40,"area":null},{"id":"2404.00722","title":"DRCT: Saving Image Super-resolution away from Information Bottleneck","created":"2024-03-31","cited_by_count":40,"area":null},{"id":"2404.09790","title":"NTIRE 2024 Challenge on Image Super-Resolution (x4): Methods and Results","created":"2024-04-15","cited_by_count":40,"area":null},{"id":"2203.07319","title":"GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priors","created":"2022-03-14","cited_by_count":39,"area":null},{"id":"2206.09479","title":"StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesis","created":"2022-06-19","cited_by_count":38,"area":null},{"id":"2402.02333","title":"Copyright Protection in Generative AI: A Technical Perspective","created":"2024-02-04","cited_by_count":38,"area":null},{"id":"2405.07023","title":"Efficient Real-world Image Super-Resolution Via Adaptive Directional Gradient Convolution","created":"2024-05-11","cited_by_count":37,"area":null},{"id":"2503.11221","title":"Toward Generalized Image Quality Assessment: Relaxing the Perfect Reference Quality Assumption","created":"2025-03-14","cited_by_count":35,"area":null},{"id":"2105.07809","title":"Learned Smartphone ISP on Mobile NPUs with Deep Learning, Mobile AI 2021 Challenge: Report","created":"2021-05-17","cited_by_count":34,"area":null},{"id":"2109.01349","title":"Dual-Camera Super-Resolution with Aligned Attention Modules","created":"2021-09-03","cited_by_count":34,"area":null},{"id":"2303.05156","title":"Local Implicit Normalizing Flow for Arbitrary-Scale Image Super-Resolution","created":"2023-03-09","cited_by_count":34,"area":null},{"id":"2312.03014","title":"Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey","created":"2023-12-05","cited_by_count":34,"area":null},{"id":"2403.10075","title":"A survey of synthetic data augmentation methods in computer vision","created":"2024-03-15","cited_by_count":34,"area":null},{"id":"2112.06536","title":"SphereSR: 360{\\deg} Image Super-Resolution with Arbitrary Projection via Continuous Spherical Image Representation","created":"2021-12-13","cited_by_count":33,"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":"2110.08521","title":"Locally Adaptive Structure and Texture Similarity for Image Quality Assessment","created":"2021-10-16","cited_by_count":32,"area":null},{"id":"2204.06504","title":"DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization","created":"2022-04-13","cited_by_count":32,"area":null},{"id":"2204.08332","title":"BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment","created":"2022-04-18","cited_by_count":32,"area":null},{"id":"2208.05424","title":"Hard-Constrained Deep Learning for Climate Downscaling","created":"2022-08-08","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":"2203.17276","title":"Bringing Old Films Back to Life","created":"2022-03-31","cited_by_count":31,"area":null},{"id":"2301.10937","title":"Super-Resolution Analysis via Machine Learning: A Survey for Fluid Flows","created":"2023-01-26","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":"2103.15295","title":"Best-Buddy GANs for Highly Detailed Image Super-Resolution","created":"2021-03-29","cited_by_count":30,"area":null}],"next_cursor":"100"}