{"total":154,"rows":[{"id":"2104.07636","title":"Image Super-Resolution via Iterative Refinement","created":"2021-04-15","cited_by_count":1511,"area":null},{"id":"2101.05278","title":"GAN Inversion: A Survey","created":"2021-01-14","cited_by_count":367,"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":"2109.05923","title":"Low-Light Image Enhancement with Normalizing Flow","created":"2021-09-13","cited_by_count":185,"area":null},{"id":"2301.11699","title":"Image Restoration with Mean-Reverting Stochastic Differential Equations","created":"2023-01-27","cited_by_count":183,"area":null},{"id":"2108.03690","title":"Enhanced Invertible Encoding for Learned Image Compression","created":"2021-08-08","cited_by_count":105,"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":"2103.15977","title":"Flow-based Kernel Prior with Application to Blind Super-Resolution","created":"2021-03-29","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":"2212.12678","title":"Towards Blind Watermarking: Combining Invertible and Non-invertible Mechanisms","created":"2022-12-24","cited_by_count":61,"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":"2107.02555","title":"A Theory of the Distortion-Perception Tradeoff in Wasserstein Space","created":"2021-07-06","cited_by_count":52,"area":null},{"id":"2105.04551","title":"Stochastic Image-to-Video Synthesis using cINNs","created":"2021-05-10","cited_by_count":49,"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":"2401.03395","title":"Deep Learning-based Image and Video Inpainting: A Survey","created":"2024-01-07","cited_by_count":44,"area":null},{"id":"2107.02790","title":"iPOKE: Poking a Still Image for Controlled Stochastic Video Synthesis","created":"2021-07-06","cited_by_count":42,"area":null},{"id":"2203.04946","title":"Do better ImageNet classifiers assess perceptual similarity better?","created":"2022-03-09","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":"2407.12431","title":"GLARE: Low Light Image Enhancement via Generative Latent Feature based Codebook Retrieval","created":"2024-07-17","cited_by_count":33,"area":null},{"id":"2208.05424","title":"Hard-Constrained Deep Learning for Climate Downscaling","created":"2022-08-08","cited_by_count":32,"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":"2104.10325","title":"SRWarp: Generalized Image Super-Resolution under Arbitrary Transformation","created":"2021-04-21","cited_by_count":27,"area":null},{"id":"2105.01237","title":"COMISR: Compression-Informed Video Super-Resolution","created":"2021-05-04","cited_by_count":26,"area":null},{"id":"2201.06578","title":"Collapse by Conditioning: Training Class-conditional GANs with Limited Data","created":"2022-01-17","cited_by_count":25,"area":null},{"id":"2310.03054","title":"Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel","created":"2023-10-04","cited_by_count":25,"area":null},{"id":"2404.06692","title":"Perception-Oriented Video Frame Interpolation via Asymmetric Blending","created":"2024-04-10","cited_by_count":23,"area":null},{"id":"2106.03839","title":"NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results","created":"2021-06-07","cited_by_count":22,"area":null},{"id":"2205.12021","title":"PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization","created":"2022-05-24","cited_by_count":22,"area":null},{"id":"2404.00874","title":"DiSR-NeRF: Diffusion-Guided View-Consistent Super-Resolution NeRF","created":"2024-04-01","cited_by_count":22,"area":null},{"id":"2406.00609","title":"SuperGaussian: Repurposing Video Models for 3D Super Resolution","created":"2024-06-02","cited_by_count":22,"area":null},{"id":"2211.13676","title":"Perception-Oriented Single Image Super-Resolution using Optimal Objective Estimation","created":"2022-11-24","cited_by_count":21,"area":null},{"id":"2304.13518","title":"Super-NeRF: View-consistent Detail Generation for NeRF super-resolution","created":"2023-04-26","cited_by_count":21,"area":null},{"id":"2106.04428","title":"Noise Conditional Flow Model for Learning the Super-Resolution Space","created":"2021-06-06","cited_by_count":19,"area":null},{"id":"2111.03231","title":"Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation","created":"2021-11-05","cited_by_count":19,"area":null},{"id":"2203.05940","title":"PD-Flow: A Point Cloud Denoising Framework with Normalizing Flows","created":"2022-03-11","cited_by_count":19,"area":null},{"id":"2210.15902","title":"Learning to Immunize Images for Tamper Localization and Self-Recovery","created":"2022-10-28","cited_by_count":19,"area":null},{"id":"2106.04090","title":"Variational AutoEncoder for Reference based Image Super-Resolution","created":"2021-06-08","cited_by_count":18,"area":null},{"id":"2109.12530","title":"Structure-Preserving Image Super-Resolution","created":"2021-09-26","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":"2107.05893","title":"PU-Flow: a Point Cloud Upsampling Network with Normalizing Flows","created":"2021-07-13","cited_by_count":17,"area":null},{"id":"2106.03135","title":"Go with the Flows: Mixtures of Normalizing Flows for Point Cloud Generation and Reconstruction","created":"2021-06-06","cited_by_count":16,"area":null},{"id":"2305.07774","title":"PanFlowNet: A Flow-Based Deep Network for Pan-sharpening","created":"2023-05-12","cited_by_count":16,"area":null},{"id":"2402.19215","title":"Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts","created":"2024-02-29","cited_by_count":16,"area":null},{"id":"2105.03085","title":"Toward Interactive Modulation for Photo-Realistic Image Restoration","created":"2021-05-07","cited_by_count":15,"area":null},{"id":"2210.04188","title":"Invertible Rescaling Network and Its Extensions","created":"2022-10-09","cited_by_count":15,"area":null},{"id":"2211.11220","title":"STGlow: A Flow-based Generative Framework with Dual Graphormer for Pedestrian Trajectory Prediction","created":"2022-11-21","cited_by_count":14,"area":null},{"id":"2104.04785","title":"Generating Physically-Consistent Satellite Imagery for Climate Visualizations","created":"2021-04-10","cited_by_count":13,"area":null},{"id":"2106.03959","title":"Generative Flows with Invertible Attentions","created":"2021-06-07","cited_by_count":13,"area":null},{"id":"2109.04242","title":"IICNet: A Generic Framework for Reversible Image Conversion","created":"2021-09-09","cited_by_count":13,"area":null},{"id":"2211.08944","title":"Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality","created":"2022-11-16","cited_by_count":13,"area":null},{"id":"2310.16047","title":"From Posterior Sampling to Meaningful Diversity in Image Restoration","created":"2023-10-24","cited_by_count":12,"area":null},{"id":"2109.08770","title":"WiSoSuper: Benchmarking Super-Resolution Methods on Wind and Solar Data","created":"2021-09-17","cited_by_count":11,"area":null},{"id":"2110.14196","title":"From Image to Imuge: Immunized Image Generation","created":"2021-10-27","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":"2406.17256","title":"Disentangled Motion Modeling for Video Frame Interpolation","created":"2024-06-25","cited_by_count":11,"area":null},{"id":"2111.03649","title":"Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-resolution","created":"2021-11-05","cited_by_count":10,"area":null},{"id":"2201.08157","title":"WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution","created":"2022-01-20","cited_by_count":10,"area":null},{"id":"2306.01630","title":"A Conditional Normalizing Flow for Accelerated Multi-Coil MR Imaging","created":"2023-06-02","cited_by_count":10,"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":"2111.04639","title":"S3RP: Self-Supervised Super-Resolution and Prediction for Advection-Diffusion Process","created":"2021-11-08","cited_by_count":9,"area":null},{"id":"2201.04898","title":"Flexible Style Image Super-Resolution using Conditional Objective","created":"2022-01-13","cited_by_count":9,"area":null},{"id":"2209.05054","title":"High-Fidelity Variable-Rate Image Compression via Invertible Activation Transformation","created":"2022-09-12","cited_by_count":9,"area":null},{"id":"2209.12433","title":"Deep generative model super-resolves spatially correlated multiregional climate data","created":"2022-09-26","cited_by_count":9,"area":null},{"id":"2303.02353","title":"Self-Asymmetric Invertible Network for Compression-Aware Image Rescaling","created":"2023-03-04","cited_by_count":9,"area":null},{"id":"2403.01124","title":"Text-guided Explorable Image Super-resolution","created":"2024-03-02","cited_by_count":9,"area":null},{"id":"2403.18730","title":"Towards Image Ambient Lighting Normalization","created":"2024-03-27","cited_by_count":9,"area":null},{"id":"2404.02986","title":"Universal Functional Regression with Neural Operator Flows","created":"2024-04-03","cited_by_count":9,"area":null},{"id":"2103.13389","title":"Generating Novel Scene Compositions from Single Images and Videos","created":"2021-03-24","cited_by_count":8,"area":null},{"id":"2204.09679","title":"FS-NCSR: Increasing Diversity of the Super-Resolution Space via Frequency Separation and Noise-Conditioned Normalizing Flow","created":"2022-04-20","cited_by_count":8,"area":null},{"id":"2207.05430","title":"Learning Diverse Tone Styles for Image Retouching","created":"2022-07-12","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":"2212.04319","title":"On the Robustness of Normalizing Flows for Inverse Problems in Imaging","created":"2022-12-08","cited_by_count":8,"area":null},{"id":"2308.04605","title":"PSRFlow: Probabilistic Super Resolution with Flow-Based Models for Scientific Data","created":"2023-08-08","cited_by_count":8,"area":null},{"id":"2103.14373","title":"D2C-SR: A Divergence to Convergence Approach for Real-World Image Super-Resolution","created":"2021-03-26","cited_by_count":7,"area":null},{"id":"2302.12491","title":"Joint Learning of Blind Super-Resolution and Crack Segmentation for Realistic Degraded Images","created":"2023-02-24","cited_by_count":7,"area":null},{"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":"2403.10988","title":"Boosting Flow-based Generative Super-Resolution Models via Learned Prior","created":"2024-03-16","cited_by_count":7,"area":null},{"id":"2504.18524","title":"Augmenting Perceptual Super-Resolution via Image Quality Predictors","created":"2025-04-25","cited_by_count":7,"area":null},{"id":"2112.13191","title":"DSRGAN: Detail Prior-Assisted Perceptual Single Image Super-Resolution via Generative Adversarial Networks","created":"2021-12-25","cited_by_count":6,"area":null},{"id":"2201.01034","title":"Uncovering the Over-smoothing Challenge in Image Super-Resolution: Entropy-based Quantification and Contrastive Optimization","created":"2022-01-04","cited_by_count":6,"area":null},{"id":"2210.08176","title":"Invertible Monotone Operators for Normalizing Flows","created":"2022-10-15","cited_by_count":6,"area":null},{"id":"2507.14367","title":"Hallucination Score: Towards Mitigating Hallucinations in Generative Image Super-Resolution","created":"2025-07-18","cited_by_count":6,"area":null},{"id":"2104.09895","title":"Posterior Sampling for Image Restoration using Explicit Patch Priors","created":"2021-04-20","cited_by_count":5,"area":null},{"id":"2106.09003","title":"Invertible Attention","created":"2021-06-16","cited_by_count":5,"area":null},{"id":"2112.07315","title":"Kernel-aware Burst Blind Super-Resolution","created":"2021-12-14","cited_by_count":5,"area":null},{"id":"2204.12819","title":"Conformer and Blind Noisy Students for Improved Image Quality Assessment","created":"2022-04-27","cited_by_count":5,"area":null},{"id":"2209.15165","title":"Distilling Style from Image Pairs for Global Forward and Inverse Tone Mapping","created":"2022-09-30","cited_by_count":5,"area":null},{"id":"2212.04666","title":"Neural Volume Super-Resolution","created":"2022-12-09","cited_by_count":5,"area":null},{"id":"2305.10732","title":"BlindHarmony: \"Blind\" Harmonization for MR Images via Flow model","created":"2023-05-18","cited_by_count":5,"area":null},{"id":"2306.17595","title":"RBSR: Efficient and Flexible Recurrent Network for Burst Super-Resolution","created":"2023-06-30","cited_by_count":5,"area":null},{"id":"2308.00931","title":"WaterFlow: Heuristic Normalizing Flow for Underwater Image Enhancement and Beyond","created":"2023-08-02","cited_by_count":5,"area":null},{"id":"2410.04811","title":"Learning Efficient and Effective Trajectories for Differential Equation-based Image Restoration","created":"2024-10-07","cited_by_count":5,"area":null},{"id":"2503.11787","title":"ECLARE: Efficient cross-planar learning for anisotropic resolution enhancement","created":"2025-03-14","cited_by_count":5,"area":null},{"id":"2104.08575","title":"VSpSR: Explorable Super-Resolution via Variational Sparse Representation","created":"2021-04-17","cited_by_count":4,"area":null},{"id":"2106.02531","title":"CAFLOW: Conditional Autoregressive Flows","created":"2021-06-04","cited_by_count":4,"area":null},{"id":"2106.12699","title":"Distilling the Knowledge from Conditional Normalizing Flows","created":"2021-06-24","cited_by_count":4,"area":null},{"id":"2207.11844","title":"Enhancing Image Rescaling using Dual Latent Variables in Invertible Neural Network","created":"2022-07-24","cited_by_count":4,"area":null}],"next_cursor":"100"}