{"list":"other","total":51,"rows":[{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"1801.03924","title":"The Unreasonable Effectiveness of Deep Features as a Perceptual Metric","created":"2018-01-11","cited_by_count":11177},{"id":"1503.02531","title":"Distilling the Knowledge in a Neural Network","created":"2015-03-09","cited_by_count":10324},{"id":"1608.06993","title":"Densely Connected Convolutional Networks","created":"2016-08-25","cited_by_count":6720},{"id":"2108.10257","title":"SwinIR: Image Restoration Using Swin Transformer","created":"2021-08-23","cited_by_count":1887},{"id":"1707.02921","title":"Enhanced Deep Residual Networks for Single Image Super-Resolution","created":"2017-07-10","cited_by_count":1552},{"id":"1501.00092","title":"Image Super-Resolution Using Deep Convolutional Networks","created":"2014-12-31","cited_by_count":1224},{"id":"1609.05158","title":"Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network","created":"2016-09-16","cited_by_count":1204},{"id":"2107.10833","title":"Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Data","created":"2021-07-22","cited_by_count":970},{"id":"2004.07728","title":"Image Quality Assessment: Unifying Structure and Texture Similarity","created":"2020-04-16","cited_by_count":811},{"id":"1802.08797","title":"Residual Dense Network for Image Super-Resolution","created":"2018-02-24","cited_by_count":799},{"id":"2205.14100","title":"GIT: A Generative Image-to-text Transformer for Vision and Language","created":"2022-05-27","cited_by_count":537},{"id":"2103.14006","title":"Designing a Practical Degradation Model for Deep Blind Image Super-Resolution","created":"2021-03-25","cited_by_count":529},{"id":"2205.04437","title":"Activating More Pixels in Image Super-Resolution Transformer","created":"2022-05-09","cited_by_count":438},{"id":"2003.03808","title":"PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models","created":"2020-03-08","cited_by_count":358},{"id":"1510.04389","title":"Sketch-based Manga Retrieval using Manga109 Dataset","created":"2015-10-15","cited_by_count":329},{"id":"2108.05054","title":"Rethinking Coarse-to-Fine Approach in Single Image Deblurring","created":"2021-08-11","cited_by_count":326},{"id":"1511.04491","title":"Deeply-Recursive Convolutional Network for Image Super-Resolution","created":"2015-11-14","cited_by_count":317},{"id":"2206.11253","title":"Towards Robust Blind Face Restoration with Codebook Lookup Transformer","created":"2022-06-22","cited_by_count":231},{"id":"2308.03060","title":"TOPIQ: A Top-down Approach from Semantics to Distortions for Image Quality Assessment","created":"2023-08-06","cited_by_count":226},{"id":"2003.13659","title":"Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulation","created":"2020-03-30","cited_by_count":225},{"id":"1904.03377","title":"Blind Super-Resolution With Iterative Kernel Correction","created":"2019-04-06","cited_by_count":203},{"id":"1308.3052","title":"Gradient Magnitude Similarity Deviation: A Highly Efficient Perceptual Image Quality Index","created":"2013-08-14","cited_by_count":195},{"id":"2104.00416","title":"Unsupervised Degradation Representation Learning for Blind Super-Resolution","created":"2021-04-01","cited_by_count":177},{"id":"1612.05890","title":"Learning a No-Reference Quality Metric for Single-Image Super-Resolution","created":"2016-12-18","cited_by_count":144},{"id":"2005.00305","title":"Defocus Deblurring Using Dual-Pixel Data","created":"2020-05-01","cited_by_count":139},{"id":"2010.02631","title":"Unfolding the Alternating Optimization for Blind Super Resolution","created":"2020-10-06","cited_by_count":129},{"id":"1911.07850","title":"Frequency Separation for Real-World Super-Resolution","created":"2019-11-18","cited_by_count":115},{"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},{"id":"2008.00418","title":"Blind Face Restoration via Deep Multi-scale Component Dictionaries","created":"2020-08-02","cited_by_count":106},{"id":"2202.13142","title":"Real-World Blind Super-Resolution via Feature Matching with Implicit High-Resolution Priors","created":"2022-02-26","cited_by_count":100},{"id":"2009.08709","title":"Progressive Semantic-Aware Style Transformation for Blind Face Restoration","created":"2020-09-18","cited_by_count":99},{"id":"2204.10485","title":"Attentions Help CNNs See Better: Attention-based Hybrid Image Quality Assessment Network","created":"2022-04-22","cited_by_count":57},{"id":"2207.13686","title":"Shift-tolerant Perceptual Similarity Metric","created":"2022-07-27","cited_by_count":44},{"id":"2108.07948","title":"Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment","created":"2021-08-18","cited_by_count":41},{"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},{"id":"2403.05049","title":"XPSR: Cross-modal Priors for Diffusion-based Image Super-Resolution","created":"2024-03-08","cited_by_count":41},{"id":"2404.09790","title":"NTIRE 2024 Challenge on Image Super-Resolution (x4): Methods and Results","created":"2024-04-15","cited_by_count":40},{"id":"2205.05065","title":"MM-RealSR: Metric Learning based Interactive Modulation for Real-World Super-Resolution","created":"2022-05-10","cited_by_count":33},{"id":"2206.07038","title":"AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos","created":"2022-06-14","cited_by_count":23},{"id":"2304.06440","title":"Zoom-VQA: Patches, Frames and Clips Integration for Video Quality Assessment","created":"2023-04-13","cited_by_count":21},{"id":"2308.00729","title":"Ada-DQA: Adaptive Diverse Quality-aware Feature Acquisition for Video Quality Assessment","created":"2023-08-01","cited_by_count":20},{"id":"2303.09735","title":"SRFormerV2: Taking a Closer Look at Permuted Self-Attention for Image Super-Resolution","created":"2023-03-17","cited_by_count":18},{"id":"2307.16813","title":"Capturing Co-existing Distortions in User-Generated Content for No-reference Video Quality Assessment","created":"2023-07-31","cited_by_count":18},{"id":"2403.10362","title":"CPGA: Coding Priors-Guided Aggregation Network for Compressed Video Quality Enhancement","created":"2024-03-15","cited_by_count":17},{"id":"2405.17765","title":"PTM-VQA: Efficient Video Quality Assessment Leveraging Diverse PreTrained Models from the Wild","created":"2024-05-28","cited_by_count":17},{"id":"2307.08544","title":"Reconstructed Convolution Module Based Look-Up Tables for Efficient Image Super-Resolution","created":"2023-07-17","cited_by_count":15},{"id":"2210.06924","title":"Scene Text Image Super-Resolution via Content Perceptual Loss and Criss-Cross Transformer Blocks","created":"2022-10-13","cited_by_count":8},{"id":"2403.11451","title":"CasSR: Activating Image Power for Real-World Image Super-Resolution","created":"2024-03-18","cited_by_count":7},{"id":"2310.17188","title":"Blind Image Super-resolution with Rich Texture-Aware Codebooks","created":"2023-10-26","cited_by_count":6},{"id":"2306.11334","title":"Depth and DOF Cues Make A Better Defocus Blur Detector","created":"2023-06-20","cited_by_count":4}],"next_cursor":null}