{"list":"other","total":55,"rows":[{"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":"2304.07193","title":"DINOv2: Learning Robust Visual Features without Supervision","created":"2023-04-14","cited_by_count":7974},{"id":"2111.06377","title":"Masked Autoencoders Are Scalable Vision Learners","created":"2021-11-11","cited_by_count":7403},{"id":"1503.03585","title":"Deep Unsupervised Learning using Nonequilibrium Thermodynamics","created":"2015-03-12","cited_by_count":7058},{"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":"2102.12092","title":"Zero-Shot Text-to-Image Generation","created":"2021-02-24","cited_by_count":4288},{"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":"2201.03545","title":"A ConvNet for the 2020s","created":"2022-01-10","cited_by_count":3579},{"id":"1606.08415","title":"Gaussian Error Linear Units (GELUs)","created":"2016-06-27","cited_by_count":3502},{"id":"2303.15343","title":"Sigmoid Loss for Language Image Pre-Training","created":"2023-03-27","cited_by_count":3109},{"id":"1905.04899","title":"CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features","created":"2019-05-13","cited_by_count":2884},{"id":"1506.03365","title":"LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop","created":"2015-06-10","cited_by_count":1355},{"id":"1610.01644","title":"Understanding intermediate layers using linear classifier probes","created":"2016-10-05","cited_by_count":1353},{"id":"1411.1792","title":"How transferable are features in deep neural networks?","created":"2014-11-06","cited_by_count":1225},{"id":"1912.11035","title":"CNN-generated images are surprisingly easy to spot... for now","created":"2019-12-23","cited_by_count":847},{"id":"2003.08685","title":"Leveraging Frequency Analysis for Deep Fake Image Recognition","created":"2020-03-19","cited_by_count":504},{"id":"2302.10174","title":"Towards Universal Fake Image Detectors that Generalize Across Generative Models","created":"2023-02-20","cited_by_count":490},{"id":"2105.10497","title":"Intriguing Properties of Vision Transformers","created":"2021-05-21","cited_by_count":446},{"id":"2303.09295","title":"DIRE for Diffusion-Generated Image Detection","created":"2023-03-16","cited_by_count":390},{"id":"2103.16302","title":"Rethinking Spatial Dimensions of Vision Transformers","created":"2021-03-30","cited_by_count":361},{"id":"2306.08571","title":"GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image","created":"2023-06-14","cited_by_count":321},{"id":"2202.06709","title":"How Do Vision Transformers Work?","created":"2022-02-14","cited_by_count":307},{"id":"2008.10588","title":"What makes fake images detectable? Understanding properties that generalize","created":"2020-08-24","cited_by_count":273},{"id":"2002.00133","title":"Global Texture Enhancement for Fake Face Detection in the Wild","created":"2020-02-01","cited_by_count":220},{"id":"2210.11466","title":"Surgical Fine-Tuning Improves Adaptation to Distribution Shifts","created":"2022-10-20","cited_by_count":205},{"id":"2312.16649","title":"Forgery-aware Adaptive Transformer for Generalizable Synthetic Image Detection","created":"2023-12-27","cited_by_count":182},{"id":"2304.13949","title":"UCF: Uncovering Common Features for Generalizable Deepfake Detection","created":"2023-04-27","cited_by_count":180},{"id":"2312.00195","title":"Raising the Bar of AI-generated Image Detection with CLIP","created":"2023-11-30","cited_by_count":164},{"id":"1907.10823","title":"Enhancing Adversarial Example Transferability with an Intermediate Level Attack","created":"2019-07-23","cited_by_count":140},{"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":"1810.00113","title":"Predicting the Generalization Gap in Deep Networks with Margin Distributions","created":"2018-09-28","cited_by_count":113},{"id":"2305.00729","title":"What Do Self-Supervised Vision Transformers Learn?","created":"2023-05-01","cited_by_count":93},{"id":"2401.13856","title":"LAA-Net: Localized Artifact Attention Network for Quality-Agnostic and Generalizable Deepfake Detection","created":"2024-01-24","cited_by_count":89},{"id":"2201.03529","title":"Head2Toe: Utilizing Intermediate Representations for Better Transfer Learning","created":"2022-01-10","cited_by_count":83},{"id":"2202.03347","title":"FrePGAN: Robust Deepfake Detection Using Frequency-level Perturbations","created":"2022-02-07","cited_by_count":75},{"id":"2402.17229","title":"Preserving Fairness Generalization in Deepfake Detection","created":"2024-02-27","cited_by_count":70},{"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":"2109.00911","title":"BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection","created":"2021-08-16","cited_by_count":60},{"id":"2310.15150","title":"Online Detection of AI-Generated Images","created":"2023-10-23","cited_by_count":55},{"id":"2307.06272","title":"Exposing the Fake: Effective Diffusion-Generated Images Detection","created":"2023-07-12","cited_by_count":48},{"id":"2403.17608","title":"Fake or JPEG? Revealing Common Biases in Generated Image Detection Datasets","created":"2024-03-26","cited_by_count":43},{"id":"2207.02803","title":"Delving into Sequential Patches for Deepfake Detection","created":"2022-07-06","cited_by_count":41},{"id":"2010.06498","title":"Cross-Domain Few-Shot Learning by Representation Fusion","created":"2020-10-13","cited_by_count":32},{"id":"2303.10762","title":"Deep Image Fingerprint: Towards Low Budget Synthetic Image Detection and Model Lineage Analysis","created":"2023-03-19","cited_by_count":30},{"id":"2406.04932","title":"Faster Than Lies: Real-time Deepfake Detection using Binary Neural Networks","created":"2024-06-07","cited_by_count":27},{"id":"2405.13360","title":"How to Trace Latent Generative Model Generated Images without Artificial Watermark?","created":"2024-05-22","cited_by_count":26},{"id":"2410.14516","title":"Do LLMs \"know\" internally when they follow instructions?","created":"2024-10-18","cited_by_count":26},{"id":"2404.04883","title":"Mixture of Low-rank Experts for Transferable AI-Generated Image Detection","created":"2024-04-07","cited_by_count":21},{"id":"2006.11863","title":"Generalized Zero and Few-Shot Transfer for Facial Forgery Detection","created":"2020-06-21","cited_by_count":18},{"id":"2504.05461","title":"Intermediate Layer Classifiers for OOD generalization","created":"2025-04-07","cited_by_count":14}],"next_cursor":null}