{"list":"other","total":94,"rows":[{"id":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"id":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"2106.09685","title":"LoRA: Low-Rank Adaptation of Large Language Models","created":"2021-06-17","cited_by_count":14380},{"id":"1801.03924","title":"The Unreasonable Effectiveness of Deep Features as a Perceptual Metric","created":"2018-01-11","cited_by_count":11177},{"id":"2011.13456","title":"Score-Based Generative Modeling through Stochastic Differential Equations","created":"2020-11-26","cited_by_count":9122},{"id":"2105.05233","title":"Diffusion Models Beat GANs on Image Synthesis","created":"2021-05-11","cited_by_count":8255},{"id":"2302.05543","title":"Adding Conditional Control to Text-to-Image Diffusion Models","created":"2023-02-10","cited_by_count":5503},{"id":"1711.00937","title":"Neural Discrete Representation Learning","created":"2017-11-02","cited_by_count":4712},{"id":"1611.07004","title":"Image-to-Image Translation with Conditional Adversarial Networks","created":"2016-11-21","cited_by_count":4527},{"id":"2307.01952","title":"SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis","created":"2023-07-04","cited_by_count":4356},{"id":"2012.09841","title":"Taming Transformers for High-Resolution Image Synthesis","created":"2020-12-17","cited_by_count":3253},{"id":"1609.04802","title":"Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network","created":"2016-09-15","cited_by_count":1908},{"id":"2108.10257","title":"SwinIR: Image Restoration Using Swin Transformer","created":"2021-08-23","cited_by_count":1887},{"id":"2303.01469","title":"Consistency Models","created":"2023-03-02","cited_by_count":1822},{"id":"2104.07636","title":"Image Super-Resolution via Iterative Refinement","created":"2021-04-15","cited_by_count":1511},{"id":"2302.08453","title":"T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models","created":"2023-02-16","cited_by_count":1351},{"id":"1807.02758","title":"Image Super-Resolution Using Very Deep Residual Channel Attention Networks","created":"2018-07-08","cited_by_count":1264},{"id":"2305.16213","title":"ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation","created":"2023-05-25","cited_by_count":1219},{"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":"2108.05997","title":"MUSIQ: Multi-scale Image Quality Transformer","created":"2021-08-12","cited_by_count":1081},{"id":"2311.18828","title":"One-step Diffusion with Distribution Matching Distillation","created":"2023-11-30","cited_by_count":1019},{"id":"2207.12396","title":"Exploring CLIP for Assessing the Look and Feel of Images","created":"2022-07-25","cited_by_count":991},{"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":"2310.04378","title":"Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference","created":"2023-10-06","cited_by_count":846},{"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":"2311.17042","title":"Adversarial Diffusion Distillation","created":"2023-11-28","cited_by_count":759},{"id":"2210.03142","title":"On Distillation of Guided Diffusion Models","created":"2022-10-06","cited_by_count":725},{"id":"2405.14867","title":"Improved Distribution Matching Distillation for Fast Image Synthesis","created":"2024-05-23","cited_by_count":684},{"id":"2103.14006","title":"Designing a Practical Degradation Model for Deep Blind Image Super-Resolution","created":"2021-03-25","cited_by_count":529},{"id":"2204.08958","title":"MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment","created":"2022-04-19","cited_by_count":522},{"id":"2112.07804","title":"Tackling the Generative Learning Trilemma with Denoising Diffusion GANs","created":"2021-12-15","cited_by_count":516},{"id":"2305.07015","title":"Exploiting Diffusion Prior for Real-World Image Super-Resolution","created":"2023-05-11","cited_by_count":489},{"id":"2310.02279","title":"Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion","created":"2023-10-01","cited_by_count":459},{"id":"2205.04437","title":"Activating More Pixels in Image Super-Resolution Transformer","created":"2022-05-09","cited_by_count":438},{"id":"2104.14951","title":"SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models","created":"2021-04-30","cited_by_count":415},{"id":"1904.00523","title":"Toward Real-World Single Image Super-Resolution: A New Benchmark and A New Model","created":"2019-04-01","cited_by_count":403},{"id":"2309.06380","title":"InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation","created":"2023-09-12","cited_by_count":395},{"id":"2307.12348","title":"ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shifting","created":"2023-07-23","cited_by_count":365},{"id":"2312.00858","title":"DeepCache: Accelerating Diffusion Models for Free","created":"2023-12-01","cited_by_count":359},{"id":"2101.04061","title":"Towards Real-World Blind Face Restoration with Generative Facial Prior","created":"2021-01-11","cited_by_count":349},{"id":"2101.02388","title":"Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed","created":"2021-01-07","cited_by_count":348},{"id":"2311.16518","title":"SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution","created":"2023-11-27","cited_by_count":315},{"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},{"id":"2403.12015","title":"Fast High-Resolution Image Synthesis with Latent Adversarial Diffusion Distillation","created":"2024-03-18","cited_by_count":279},{"id":"2402.13929","title":"SDXL-Lightning: Progressive Adversarial Diffusion Distillation","created":"2024-02-21","cited_by_count":266},{"id":"2308.15070","title":"DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior","created":"2023-08-29","cited_by_count":257},{"id":"2308.14469","title":"Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization","created":"2023-08-28","cited_by_count":254},{"id":"2008.01928","title":"Component Divide-and-Conquer for Real-World Image Super-Resolution","created":"2020-08-05","cited_by_count":246},{"id":"2406.08177","title":"One-Step Effective Diffusion Network for Real-World Image Super-Resolution","created":"2024-06-12","cited_by_count":246},{"id":"2311.14760","title":"SinSR: Diffusion-Based Image Super-Resolution in a Single Step","created":"2023-11-23","cited_by_count":238},{"id":"2306.00980","title":"SnapFusion: Text-to-Image Diffusion Model on Mobile Devices within Two Seconds","created":"2023-06-01","cited_by_count":227},{"id":"1602.02644","title":"Generating Images with Perceptual Similarity Metrics based on Deep Networks","created":"2016-02-08","cited_by_count":222},{"id":"2206.02262","title":"Diffusion-GAN: Training GANs with Diffusion","created":"2022-06-05","cited_by_count":205},{"id":"2105.06070","title":"GAN Prior Embedded Network for Blind Face Restoration in the Wild","created":"2021-05-13","cited_by_count":197},{"id":"2305.10924","title":"Structural Pruning for Diffusion Models","created":"2023-05-18","cited_by_count":195},{"id":"2301.11699","title":"Image Restoration with Mean-Reverting Stochastic Differential Equations","created":"2023-01-27","cited_by_count":183},{"id":"2311.09257","title":"UFOGen: You Forward Once Large Scale Text-to-Image Generation via Diffusion GANs","created":"2023-11-14","cited_by_count":166},{"id":"2303.11435","title":"Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration","created":"2023-03-20","cited_by_count":165},{"id":"2404.13686","title":"Hyper-SD: Trajectory Segmented Consistency Model for Efficient Image Synthesis","created":"2024-04-21","cited_by_count":156},{"id":"2303.04248","title":"TRACT: Denoising Diffusion Models with Transitive Closure Time-Distillation","created":"2023-03-07","cited_by_count":116},{"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":"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":"2306.05544","title":"BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping","created":"2023-06-08","cited_by_count":98},{"id":"2405.07510","title":"PeRFlow: Piecewise Rectified Flow as Universal Plug-and-Play Accelerator","created":"2024-05-13","cited_by_count":97},{"id":"2203.14216","title":"Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution","created":"2022-03-27","cited_by_count":96},{"id":"2405.05967","title":"Distilling Diffusion Models into Conditional GANs","created":"2024-05-09","cited_by_count":78},{"id":"2409.17058","title":"Degradation-Guided One-Step Image Super-Resolution with Diffusion Priors","created":"2024-09-25","cited_by_count":69},{"id":"2403.06807","title":"Multistep Consistency Models","created":"2024-03-11","cited_by_count":67},{"id":"2404.01717","title":"AddSR: Accelerating Diffusion-based Blind Super-Resolution with Adversarial Diffusion Distillation","created":"2024-04-02","cited_by_count":66},{"id":"2403.07319","title":"Efficient Diffusion Model for Image Restoration by Residual Shifting","created":"2024-03-12","cited_by_count":64},{"id":"2404.11098","title":"LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models","created":"2024-04-17","cited_by_count":53},{"id":"2402.19159","title":"Trajectory Consistency Distillation: Improved Latent Consistency Distillation by Semi-Linear Consistency Function with Trajectory Mapping","created":"2024-02-29","cited_by_count":46},{"id":"2408.14176","title":"SwiftBrush v2: Make Your One-step Diffusion Model Better Than Its Teacher","created":"2024-08-26","cited_by_count":45},{"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":"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},{"id":"2407.12718","title":"SlimFlow: Training Smaller One-Step Diffusion Models with Rectified Flow","created":"2024-07-17","cited_by_count":30},{"id":"2405.14822","title":"PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher","created":"2024-05-23","cited_by_count":27},{"id":"2403.12931","title":"You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs","created":"2024-03-19","cited_by_count":26},{"id":"2401.17258","title":"You Only Need One Step: Fast Super-Resolution with Stable Diffusion via Scale Distillation","created":"2024-01-30","cited_by_count":24},{"id":"2403.16627","title":"SDXS: Real-Time One-Step Latent Diffusion Models with Image Conditions","created":"2024-03-25","cited_by_count":24},{"id":"2207.09313","title":"Content-aware Scalable Deep Compressed Sensing","created":"2022-07-19","cited_by_count":21},{"id":"2406.05723","title":"Binarized Diffusion Model for Image Super-Resolution","created":"2024-06-09","cited_by_count":18},{"id":"2408.07476","title":"One Step Diffusion-based Super-Resolution with Time-Aware Distillation","created":"2024-08-14","cited_by_count":17},{"id":"2105.03085","title":"Toward Interactive Modulation for Photo-Realistic Image Restoration","created":"2021-05-07","cited_by_count":15},{"id":"2404.13903","title":"Accelerating Image Generation with Sub-path Linear Approximation Model","created":"2024-04-22","cited_by_count":14},{"id":"2406.06649","title":"2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution","created":"2024-06-10","cited_by_count":14},{"id":"2409.17778","title":"Taming Diffusion Prior for Image Super-Resolution with Domain Shift SDEs","created":"2024-09-26","cited_by_count":13},{"id":"2403.17006","title":"Invertible Diffusion Models for Compressed Sensing","created":"2024-03-25","cited_by_count":12},{"id":"2308.13777","title":"Self-Supervised Scalable Deep Compressed Sensing","created":"2023-08-26","cited_by_count":8},{"id":"2410.17752","title":"AdaDiffSR: Adaptive Region-aware Dynamic Acceleration Diffusion Model for Real-World Image Super-Resolution","created":"2024-10-23","cited_by_count":8},{"id":"2410.05799","title":"SeeClear: Semantic Distillation Enhances Pixel Condensation for Video Super-Resolution","created":"2024-10-08","cited_by_count":3}],"next_cursor":null}