{"total":122,"rows":[{"id":"2203.06697","title":"Efficient Long-Range Attention Network for Image Super-resolution","created":"2022-03-13","cited_by_count":151,"area":null},{"id":"2108.11084","title":"Transformer for Single Image Super-Resolution","created":"2021-08-25","cited_by_count":150,"area":null},{"id":"2304.10244","title":"Omni Aggregation Networks for Lightweight Image Super-Resolution","created":"2023-04-20","cited_by_count":62,"area":null},{"id":"2302.13800","title":"Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution","created":"2023-02-27","cited_by_count":57,"area":null},{"id":"2404.10343","title":"The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report","created":"2024-04-16","cited_by_count":57,"area":null},{"id":"2205.07514","title":"Residual Local Feature Network for Efficient Super-Resolution","created":"2022-05-16","cited_by_count":53,"area":null},{"id":"2104.14854","title":"NTIRE 2021 Challenge on Image Deblurring","created":"2021-04-30","cited_by_count":50,"area":null},{"id":"2211.11436","title":"N-Gram in Swin Transformers for Efficient Lightweight Image Super-Resolution","created":"2022-11-21","cited_by_count":46,"area":null},{"id":"2205.05996","title":"Blueprint Separable Residual Network for Efficient Image Super-Resolution","created":"2022-05-12","cited_by_count":44,"area":null},{"id":"2305.13803","title":"NORM: Knowledge Distillation via N-to-One Representation Matching","created":"2023-05-23","cited_by_count":44,"area":"distill"},{"id":"2407.05878","title":"HiT-SR: Hierarchical Transformer for Efficient Image Super-Resolution","created":"2024-07-08","cited_by_count":42,"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":"2111.13924","title":"A Practical Contrastive Learning Framework for Single-Image Super-Resolution","created":"2021-11-27","cited_by_count":30,"area":null},{"id":"2402.19289","title":"CAMixerSR: Only Details Need More \"Attention\"","created":"2024-02-29","cited_by_count":30,"area":null},{"id":"2112.08655","title":"Feature Distillation Interaction Weighting Network for Lightweight Image Super-Resolution","created":"2021-12-16","cited_by_count":29,"area":"distill"},{"id":"2204.08397","title":"Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution","created":"2022-04-18","cited_by_count":27,"area":null},{"id":"2504.10686","title":"The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report","created":"2025-04-14","cited_by_count":26,"area":null},{"id":"2604.03198","title":"The Eleventh NTIRE 2026 Efficient Super-Resolution Challenge Report","created":"2026-04-03","cited_by_count":25,"area":null},{"id":"2311.12770","title":"Swift Parameter-free Attention Network for Efficient Super-Resolution","created":"2023-11-21","cited_by_count":24,"area":null},{"id":"2405.03008","title":"DVMSR: Distillated Vision Mamba for Efficient Super-Resolution","created":"2024-05-05","cited_by_count":24,"area":"ssm"},{"id":"2402.03412","title":"See More Details: Efficient Image Super-Resolution by Experts Mining","created":"2024-02-05","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":"2112.04719","title":"Learning with Nested Scene Modeling and Cooperative Architecture Search for Low-Light Vision","created":"2021-12-09","cited_by_count":22,"area":null},{"id":"2209.13131","title":"Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances","created":"2022-09-27","cited_by_count":22,"area":null},{"id":"2401.01117","title":"Q-Refine: A Perceptual Quality Refiner for AI-Generated Image","created":"2024-01-02","cited_by_count":21,"area":null},{"id":"2204.08913","title":"Self-Calibrated Efficient Transformer for Lightweight Super-Resolution","created":"2022-04-19","cited_by_count":20,"area":null},{"id":"2109.14335","title":"A Systematic Survey of Deep Learning-based Single-Image Super-Resolution","created":"2021-09-29","cited_by_count":19,"area":null},{"id":"2205.05671","title":"RepSR: Training Efficient VGG-style Super-Resolution Networks with Structural Re-Parameterization and Batch Normalization","created":"2022-05-11","cited_by_count":19,"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":"2404.16484","title":"Real-Time 4K Super-Resolution of Compressed AVIF Images. AIS 2024 Challenge Survey","created":"2024-04-25","cited_by_count":19,"area":null},{"id":"2204.08759","title":"Edge-enhanced Feature Distillation Network for Efficient Super-Resolution","created":"2022-04-19","cited_by_count":18,"area":"distill"},{"id":"2207.02796","title":"Cross-receptive Focused Inference Network for Lightweight Image Super-Resolution","created":"2022-07-06","cited_by_count":16,"area":null},{"id":"2210.05960","title":"Efficient Image Super-Resolution using Vast-Receptive-Field Attention","created":"2022-10-12","cited_by_count":16,"area":null},{"id":"2503.06896","title":"CATANet: Efficient Content-Aware Token Aggregation for Lightweight Image Super-Resolution","created":"2025-03-10","cited_by_count":16,"area":null},{"id":"2107.12679","title":"MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN","created":"2021-07-27","cited_by_count":14,"area":null},{"id":"2211.03885","title":"Learned Smartphone ISP on Mobile GPUs with Deep Learning, Mobile AI & AIM 2022 Challenge: Report","created":"2022-11-07","cited_by_count":13,"area":null},{"id":"2212.14181","title":"Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid Network","created":"2022-12-29","cited_by_count":13,"area":null},{"id":"2401.05633","title":"Transforming Image Super-Resolution: A ConvFormer-based Efficient Approach","created":"2024-01-11","cited_by_count":13,"area":null},{"id":"2108.13697","title":"Attention-based Multi-Reference Learning for Image Super-Resolution","created":"2021-08-31","cited_by_count":12,"area":null},{"id":"2204.12266","title":"Attentive Fine-Grained Structured Sparsity for Image Restoration","created":"2022-04-26","cited_by_count":12,"area":null},{"id":"2201.01458","title":"Cross-SRN: Structure-Preserving Super-Resolution Network with Cross Convolution","created":"2022-01-05","cited_by_count":10,"area":null},{"id":"2205.12633","title":"NTIRE 2022 Challenge on High Dynamic Range Imaging: Methods and Results","created":"2022-05-25","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":"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":"2209.03355","title":"Generative Adversarial Super-Resolution at the Edge with Knowledge Distillation","created":"2022-09-07","cited_by_count":9,"area":"distill"},{"id":"2407.14340","title":"Large Kernel Distillation Network for Efficient Single Image Super-Resolution","created":"2024-07-19","cited_by_count":9,"area":null},{"id":"2211.16776","title":"From Coarse to Fine: Hierarchical Pixel Integration for Lightweight Image Super-Resolution","created":"2022-11-30","cited_by_count":8,"area":null},{"id":"2305.03387","title":"AsConvSR: Fast and Lightweight Super-Resolution Network with Assembled Convolutions","created":"2023-05-05","cited_by_count":8,"area":null},{"id":"2208.11609","title":"Fast Nearest Convolution for Real-Time Efficient Image Super-Resolution","created":"2022-08-24","cited_by_count":6,"area":null},{"id":"2305.02126","title":"Bicubic++: Slim, Slimmer, Slimmest -- Designing an Industry-Grade Super-Resolution Network","created":"2023-05-03","cited_by_count":6,"area":null},{"id":"2305.11474","title":"Reciprocal Attention Mixing Transformer for Lightweight Image Restoration","created":"2023-05-19","cited_by_count":6,"area":null},{"id":"2503.04223","title":"Spiking Meets Attention: Efficient Remote Sensing Image Super-Resolution with Attention Spiking Neural Networks","created":"2025-03-06","cited_by_count":6,"area":null},{"id":"2503.13740","title":"C2D-ISR: Optimizing Attention-based Image Super-resolution from Continuous to Discrete Scales","created":"2025-03-17","cited_by_count":6,"area":null},{"id":"2105.03939","title":"Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution","created":"2021-05-09","cited_by_count":5,"area":null},{"id":"2111.13905","title":"AdaDM: Enabling Normalization for Image Super-Resolution","created":"2021-11-27","cited_by_count":5,"area":null},{"id":"2208.14839","title":"QuantNAS for super resolution: searching for efficient quantization-friendly architectures against quantization noise","created":"2022-08-31","cited_by_count":4,"area":null},{"id":"2303.04336","title":"QuickSRNet: Plain Single-Image Super-Resolution Architecture for Faster Inference on Mobile Platforms","created":"2023-03-08","cited_by_count":4,"area":null},{"id":"2103.12547","title":"A new public Alsat-2B dataset for single-image super-resolution","created":"2021-03-21","cited_by_count":3,"area":null},{"id":"2204.11463","title":"IMDeception: Grouped Information Distilling Super-Resolution Network","created":"2022-04-25","cited_by_count":3,"area":null},{"id":"2207.03367","title":"Joint Super-Resolution and Inverse Tone-Mapping: A Feature Decomposition Aggregation Network and A New Benchmark","created":"2022-07-07","cited_by_count":3,"area":null},{"id":"2211.05256","title":"Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 challenge: Report","created":"2022-11-07","cited_by_count":3,"area":null},{"id":"2404.01604","title":"WaveDH: Wavelet Sub-bands Guided ConvNet for Efficient Image Dehazing","created":"2024-04-02","cited_by_count":3,"area":null},{"id":"2404.06075","title":"LIPT: Latency-aware Image Processing Transformer","created":"2024-04-09","cited_by_count":3,"area":null},{"id":"2407.04241","title":"AnySR: Realizing Image Super-Resolution as Any-Scale, Any-Resource","created":"2024-07-05","cited_by_count":3,"area":null},{"id":"2503.10043","title":"FourierSR: A Fourier Token-based Plugin for Efficient Image Super-Resolution","created":"2025-03-13","cited_by_count":3,"area":null},{"id":"2508.11893","title":"Large Kernel Modulation Network for Efficient Image Super-Resolution","created":"2025-08-16","cited_by_count":3,"area":null},{"id":"2109.12342","title":"TreeNet: A lightweight One-Shot Aggregation Convolutional Network","created":"2021-09-25","cited_by_count":2,"area":null},{"id":"2304.01805","title":"Exploration of Lightweight Single Image Denoising with Transformers and Truly Fair Training","created":"2023-04-04","cited_by_count":2,"area":null},{"id":"2306.01500","title":"A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-Resolution","created":"2023-06-02","cited_by_count":2,"area":null},{"id":"2307.07240","title":"MaxSR: Image Super-Resolution Using Improved MaxViT","created":"2023-07-14","cited_by_count":2,"area":null},{"id":"2308.01483","title":"Efficient neural supersampling on a novel gaming dataset","created":"2023-08-03","cited_by_count":2,"area":null},{"id":"2310.10413","title":"Image super-resolution via dynamic network","created":"2023-10-16","cited_by_count":2,"area":null},{"id":"2401.08913","title":"Efficient Image Super-Resolution via Symmetric Visual Attention Network","created":"2024-01-17","cited_by_count":2,"area":null},{"id":"2508.09599","title":"BridgeTA: Bridging the Representation Gap in Knowledge Distillation via Teacher Assistant for Bird's Eye View Map Segmentation","created":"2025-08-13","cited_by_count":2,"area":"distill"},{"id":"2205.13738","title":"Image Reconstruction of Multi Branch Feature Multiplexing Fusion Network with Mixed Multi-layer Attention","created":"2022-05-27","cited_by_count":1,"area":null},{"id":"2211.09462","title":"RDRN: Recursively Defined Residual Network for Image Super-Resolution","created":"2022-11-17","cited_by_count":1,"area":null},{"id":"2301.09869","title":"Image Super-Resolution using Efficient Striped Window Transformer","created":"2023-01-24","cited_by_count":1,"area":null},{"id":"2301.10455","title":"Rate-Perception Optimized Preprocessing for Video Coding","created":"2023-01-25","cited_by_count":1,"area":null},{"id":"2302.06898","title":"Take a Prior from Other Tasks for Severe Blur Removal","created":"2023-02-14","cited_by_count":1,"area":null},{"id":"2305.17898","title":"Convolutional neural network based on sparse graph attention mechanism for MRI super-resolution","created":"2023-05-29","cited_by_count":1,"area":null},{"id":"2308.05745","title":"Iterative Reweighted Least Squares Networks With Convergence Guarantees for Solving Inverse Imaging Problems","created":"2023-08-10","cited_by_count":1,"area":null},{"id":"2402.15784","title":"IRConStyle: Image Restoration Framework Using Contrastive Learning and Style Transfer","created":"2024-02-24","cited_by_count":1,"area":null},{"id":"2405.09353","title":"Large coordinate kernel attention network for lightweight image super-resolution","created":"2024-05-15","cited_by_count":1,"area":null},{"id":"2409.03516","title":"LMLT: Low-to-high Multi-Level Vision Transformer for Image Super-Resolution","created":"2024-09-05","cited_by_count":1,"area":null},{"id":"2410.09844","title":"HASN: Hybrid Attention Separable Network for Efficient Image Super-resolution","created":"2024-10-13","cited_by_count":1,"area":null},{"id":"2509.06387","title":"Your Super Resolution Model is not Enough for Tackling Real-World Scenarios","created":"2025-09-08","cited_by_count":1,"area":null},{"id":"2602.23890","title":"DACESR: Degradation-Aware Conditional Embedding for Real-World Image Super-Resolution","created":"2026-02-27","cited_by_count":1,"area":"ssm"},{"id":"2101.05403","title":"Image deblurring based on lightweight multi-information fusion network","created":"2021-01-14","cited_by_count":0,"area":null},{"id":"2102.05450","title":"Reference-based Texture transfer for Single Image Super-resolution of Magnetic Resonance images","created":"2021-02-10","cited_by_count":0,"area":null},{"id":"2208.14600","title":"ELSR: Extreme Low-Power Super Resolution Network For Mobile Devices","created":"2022-08-31","cited_by_count":0,"area":null},{"id":"2209.08337","title":"Lightweight Spatial-Channel Adaptive Coordination of Multilevel Refinement Enhancement Network for Image Reconstruction","created":"2022-09-17","cited_by_count":0,"area":null},{"id":"2210.07818","title":"ISTA-Inspired Network for Image Super-Resolution","created":"2022-10-14","cited_by_count":0,"area":null},{"id":"2303.11701","title":"A High-Frequency Focused Network for Lightweight Single Image Super-Resolution","created":"2023-03-21","cited_by_count":0,"area":null},{"id":"2303.16411","title":"Unlocking Masked Autoencoders as Loss Function for Image and Video Restoration","created":"2023-03-29","cited_by_count":0,"area":null},{"id":"2306.02443","title":"ESTISR: Adapting Efficient Scene Text Image Super-resolution for Real-Scenes","created":"2023-06-04","cited_by_count":0,"area":null},{"id":"2307.03998","title":"Lightweight Improved Residual Network for Efficient Inverse Tone Mapping","created":"2023-07-08","cited_by_count":0,"area":null},{"id":"2308.11365","title":"Towards Clip-Free Quantized Super-Resolution Networks: How to Tame Representative Images","created":"2023-08-22","cited_by_count":0,"area":null},{"id":"2312.13396","title":"EPNet: An Efficient Pyramid Network for Enhanced Single-Image Super-Resolution with Reduced Computational Requirements","created":"2023-12-20","cited_by_count":0,"area":null},{"id":"2408.09940","title":"ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer","created":"2024-08-19","cited_by_count":0,"area":null},{"id":"2409.17597","title":"Unifying Dimensions: A Linear Adaptive Approach to Lightweight Image Super-Resolution","created":"2024-09-26","cited_by_count":0,"area":null}],"next_cursor":"100"}