{"list":"other","total":60,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"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":"1405.0312","title":"Microsoft COCO: Common Objects in Context","created":"2014-05-01","cited_by_count":17608},{"id":"2106.09685","title":"LoRA: Low-Rank Adaptation of Large Language Models","created":"2021-06-17","cited_by_count":14380},{"id":"2304.07193","title":"DINOv2: Learning Robust Visual Features without Supervision","created":"2023-04-14","cited_by_count":7974},{"id":"1503.03585","title":"Deep Unsupervised Learning using Nonequilibrium Thermodynamics","created":"2015-03-12","cited_by_count":7058},{"id":"2204.06125","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","created":"2022-04-13","cited_by_count":6585},{"id":"1607.06450","title":"Layer Normalization","created":"2016-07-21","cited_by_count":5669},{"id":"2203.00667","title":"Generative Adversarial Networks","created":"2022-03-01","cited_by_count":5627},{"id":"2307.01952","title":"SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis","created":"2023-07-04","cited_by_count":4356},{"id":"2403.03206","title":"Scaling Rectified Flow Transformers for High-Resolution Image Synthesis","created":"2024-03-05","cited_by_count":4181},{"id":"2205.14135","title":"FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness","created":"2022-05-27","cited_by_count":3673},{"id":"2112.10741","title":"GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models","created":"2021-12-20","cited_by_count":3614},{"id":"1606.08415","title":"Gaussian Error Linear Units (GELUs)","created":"2016-06-27","cited_by_count":3502},{"id":"1903.07291","title":"Semantic Image Synthesis with Spatially-Adaptive Normalization","created":"2019-03-18","cited_by_count":1299},{"id":"1711.09020","title":"StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation","created":"2017-11-24","cited_by_count":1039},{"id":"2209.04747","title":"Diffusion Models in Vision: A Survey","created":"2022-09-10","cited_by_count":1015},{"id":"1912.11035","title":"CNN-generated images are surprisingly easy to spot... for now","created":"2019-12-23","cited_by_count":847},{"id":"1711.10485","title":"AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks","created":"2017-11-28","cited_by_count":664},{"id":"2003.08685","title":"Leveraging Frequency Analysis for Deep Fake Image Recognition","created":"2020-03-19","cited_by_count":504},{"id":"2303.05511","title":"Scaling up GANs for Text-to-Image Synthesis","created":"2023-03-09","cited_by_count":492},{"id":"2302.10174","title":"Towards Universal Fake Image Detectors that Generalize Across Generative Models","created":"2023-02-20","cited_by_count":490},{"id":"2303.09295","title":"DIRE for Diffusion-Generated Image Detection","created":"2023-03-16","cited_by_count":390},{"id":"1904.01310","title":"DM-GAN: Dynamic Memory Generative Adversarial Networks for Text-to-Image Synthesis","created":"2019-04-02","cited_by_count":308},{"id":"2211.00680","title":"On the detection of synthetic images generated by diffusion models","created":"2022-11-01","cited_by_count":283},{"id":"2003.01826","title":"Watch your Up-Convolution: CNN Based Generative Deep Neural Networks are Failing to Reproduce Spectral Distributions","created":"2020-03-03","cited_by_count":280},{"id":"2303.07909","title":"Text-to-image Diffusion Models in Generative AI: A Survey","created":"2023-03-14","cited_by_count":265},{"id":"2305.18292","title":"Mix-of-Show: Decentralized Low-Rank Adaptation for Multi-Concept Customization of Diffusion Models","created":"2023-05-29","cited_by_count":261},{"id":"2002.00133","title":"Global Texture Enhancement for Fake Face Detection in the Wild","created":"2020-02-01","cited_by_count":220},{"id":"1502.04623","title":"DRAW: A Recurrent Neural Network For Image Generation","created":"2015-02-16","cited_by_count":191},{"id":"2406.19435","title":"A Sanity Check for AI-generated Image Detection","created":"2024-06-27","cited_by_count":189},{"id":"2210.06998","title":"DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Generation Models","created":"2022-10-13","cited_by_count":168},{"id":"2312.00195","title":"Raising the Bar of AI-generated Image Detection with CLIP","created":"2023-11-30","cited_by_count":164},{"id":"2401.17879","title":"AEROBLADE: Training-Free Detection of Latent Diffusion Images Using Autoencoder Reconstruction Error","created":"2024-01-31","cited_by_count":125},{"id":"2311.12397","title":"PatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection","created":"2023-11-21","cited_by_count":122},{"id":"2402.19091","title":"Leveraging Representations from Intermediate Encoder-blocks for Synthetic Image Detection","created":"2024-02-29","cited_by_count":89},{"id":"2203.13964","title":"Fusing Global and Local Features for Generalized AI-Synthesized Image Detection","created":"2022-03-26","cited_by_count":88},{"id":"2403.04279","title":"Controllable Generation with Text-to-Image Diffusion Models: A Survey","created":"2024-03-07","cited_by_count":83},{"id":"2402.00045","title":"Detecting Multimedia Generated by Large AI Models: A Survey","created":"2024-01-22","cited_by_count":76},{"id":"2206.07706","title":"Masked Frequency Modeling for Self-Supervised Visual Pre-Training","created":"2022-06-15","cited_by_count":71},{"id":"2311.17138","title":"Shadows Don't Lie and Lines Can't Bend! Generative Models don't know Projective Geometry...for now","created":"2023-11-28","cited_by_count":61},{"id":"2406.08603","title":"FakeInversion: Learning to Detect Images from Unseen Text-to-Image Models by Inverting Stable Diffusion","created":"2024-06-12","cited_by_count":61},{"id":"2409.15875","title":"Zero-Shot Detection of AI-Generated Images","created":"2024-09-24","cited_by_count":50},{"id":"2405.20112","title":"RIGID: A Training-free and Model-Agnostic Framework for Robust AI-Generated Image Detection","created":"2024-05-30","cited_by_count":36},{"id":"2207.13744","title":"Lighting (In)consistency of Paint by Text","created":"2022-07-27","cited_by_count":35},{"id":"2405.19360","title":"ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users","created":"2024-05-24","cited_by_count":35},{"id":"2206.14617","title":"Perspective (In)consistency of Paint by Text","created":"2022-06-27","cited_by_count":34},{"id":"2405.11697","title":"AMMeBa: A Large-Scale Survey and Dataset of Media-Based Misinformation In-The-Wild","created":"2024-05-19","cited_by_count":27},{"id":"2401.06506","title":"Frequency Masking for Universal Deepfake Detection","created":"2024-01-12","cited_by_count":23},{"id":"2404.18552","title":"SIDBench: A Python Framework for Reliably Assessing Synthetic Image Detection Methods","created":"2024-04-29","cited_by_count":14},{"id":"2405.00196","title":"Synthetic Image Verification in the Era of Generative AI: What Works and What Isn't There Yet","created":"2024-04-30","cited_by_count":13},{"id":"2403.11999","title":"HIRI-ViT: Scaling Vision Transformer with High Resolution Inputs","created":"2024-03-18","cited_by_count":12},{"id":"2011.02241","title":"The Forchheim Image Database for Camera Identification in the Wild","created":"2020-11-04","cited_by_count":10},{"id":"2407.15500","title":"TextureCrop: Enhancing Synthetic Image Detection through Texture-based Cropping","created":"2024-07-22","cited_by_count":9},{"id":"2408.11541","title":"Evolution of Detection Performance throughout the Online Lifespan of Synthetic Images","created":"2024-08-21","cited_by_count":8},{"id":"2410.03941","title":"AutoLoRA: AutoGuidance Meets Low-Rank Adaptation for Diffusion Models","created":"2024-10-04","cited_by_count":7},{"id":"2402.18192","title":"Misalignment-Robust Frequency Distribution Loss for Image Transformation","created":"2024-02-28","cited_by_count":6}],"next_cursor":null}