{"list":"other","total":56,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"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":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"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":"2103.14030","title":"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows","created":"2021-03-25","cited_by_count":12139},{"id":"2304.07193","title":"DINOv2: Learning Robust Visual Features without Supervision","created":"2023-04-14","cited_by_count":7974},{"id":"1905.11946","title":"EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks","created":"2019-05-28","cited_by_count":6442},{"id":"1812.04948","title":"A Style-Based Generator Architecture for Generative Adversarial Networks","created":"2018-12-12","cited_by_count":6013},{"id":"1608.03983","title":"SGDR: Stochastic Gradient Descent with Warm Restarts","created":"2016-08-13","cited_by_count":5045},{"id":"2210.08402","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","created":"2022-10-16","cited_by_count":4152},{"id":"2201.03545","title":"A ConvNet for the 2020s","created":"2022-01-10","cited_by_count":3579},{"id":"2303.15343","title":"Sigmoid Loss for Language Image Pre-Training","created":"2023-03-27","cited_by_count":3109},{"id":"2105.15203","title":"SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers","created":"2021-05-31","cited_by_count":2940},{"id":"1806.01261","title":"Relational inductive biases, deep learning, and graph networks","created":"2018-06-04","cited_by_count":1360},{"id":"1901.08971","title":"FaceForensics++: Learning to Detect Manipulated Facial Images","created":"2019-01-25","cited_by_count":1101},{"id":"1912.11035","title":"CNN-generated images are surprisingly easy to spot... for now","created":"2019-12-23","cited_by_count":847},{"id":"1909.12962","title":"Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics","created":"2019-09-27","cited_by_count":575},{"id":"2007.09355","title":"Thinking in Frequency: Face Forgery Detection by Mining Frequency-aware Clues","created":"2020-07-18","cited_by_count":523},{"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":"1912.13458","title":"Face X-ray for More General Face Forgery Detection","created":"2019-12-31","cited_by_count":470},{"id":"2303.09295","title":"DIRE for Diffusion-Generated Image Detection","created":"2023-03-16","cited_by_count":390},{"id":"2306.08571","title":"GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image","created":"2023-06-14","cited_by_count":321},{"id":"1811.00656","title":"Exposing DeepFake Videos By Detecting Face Warping Artifacts","created":"2018-11-01","cited_by_count":319},{"id":"2012.07657","title":"Lips Don't Lie: A Generalisable and Robust Approach to Face Forgery Detection","created":"2020-12-14","cited_by_count":287},{"id":"2103.12376","title":"Generalizing Face Forgery Detection with High-frequency Features","created":"2021-03-23","cited_by_count":262},{"id":"1912.13457","title":"FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping","created":"2019-12-31","cited_by_count":221},{"id":"1810.11215","title":"Capsule-Forensics: Using Capsule Networks to Detect Forged Images and Videos","created":"2018-10-26","cited_by_count":180},{"id":"2205.03409","title":"VFHQ: A High-Quality Dataset and Benchmark for Video Face Super-Resolution","created":"2022-05-06","cited_by_count":176},{"id":"2307.01426","title":"DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection","created":"2023-07-04","cited_by_count":166},{"id":"1805.04953","title":"Learning Rich Features for Image Manipulation Detection","created":"2018-05-13","cited_by_count":154},{"id":"1901.02212","title":"FakeCatcher: Detection of Synthetic Portrait Videos using Biological Signals","created":"2019-01-08","cited_by_count":145},{"id":"2406.13495","title":"DF40: Toward Next-Generation Deepfake Detection","created":"2024-06-19","cited_by_count":129},{"id":"2210.14457","title":"Implicit Identity Leakage: The Stumbling Block to Improving Deepfake Detection Generalization","created":"2022-10-26","cited_by_count":123},{"id":"2010.03743","title":"Visual News: Benchmark and Challenges in News Image Captioning","created":"2020-10-08","cited_by_count":121},{"id":"2112.08935","title":"MVSS-Net: Multi-View Multi-Scale Supervised Networks for Image Manipulation Detection","created":"2021-12-16","cited_by_count":117},{"id":"2104.06832","title":"Image Manipulation Detection by Multi-View Multi-Scale Supervision","created":"2021-04-14","cited_by_count":111},{"id":"2108.12947","title":"Learning JPEG Compression Artifacts for Image Manipulation Detection and Localization","created":"2021-08-30","cited_by_count":78},{"id":"2203.14681","title":"ObjectFormer for Image Manipulation Detection and Localization","created":"2022-03-28","cited_by_count":78},{"id":"2412.17671","title":"A Bias-Free Training Paradigm for More General AI-generated Image Detection","created":"2024-12-23","cited_by_count":67},{"id":"2009.11924","title":"Exposing GAN-generated Faces Using Inconsistent Corneal Specular Highlights","created":"2020-09-24","cited_by_count":59},{"id":"2411.04125","title":"Community Forensics: Using Thousands of Generators to Train Fake Image Detectors","created":"2024-11-06","cited_by_count":50},{"id":"2304.06870","title":"AutoSplice: A Text-prompt Manipulated Image Dataset for Media Forensics","created":"2023-04-14","cited_by_count":46},{"id":"2406.10580","title":"IMDL-BenCo: A Comprehensive Benchmark and Codebase for Image Manipulation Detection & Localization","created":"2024-06-15","cited_by_count":42},{"id":"2503.18286","title":"CO-SPY: Combining Semantic and Pixel Features to Detect Synthetic Images by AI","created":"2025-03-24","cited_by_count":42},{"id":"2412.13753","title":"Mesoscopic Insights: Orchestrating Multi-scale & Hybrid Architecture for Image Manipulation Localization","created":"2024-12-18","cited_by_count":35},{"id":"2309.14900","title":"Pre-training-free Image Manipulation Localization through Non-Mutually Exclusive Contrastive Learning","created":"2023-09-26","cited_by_count":23},{"id":"2503.19653","title":"OpenSDI: Spotting Diffusion-Generated Images in the Open World","created":"2025-03-25","cited_by_count":23},{"id":"2306.07005","title":"AI-Generated Image Detection using a Cross-Attention Enhanced Dual-Stream Network","created":"2023-06-12","cited_by_count":22},{"id":"2505.11003","title":"ForensicHub: A Unified Benchmark & Codebase for All-Domain Fake Image Detection and Localization","created":"2025-05-16","cited_by_count":22},{"id":"2311.17953","title":"Rethinking Image Editing Detection in the Era of Generative AI Revolution","created":"2023-11-29","cited_by_count":21},{"id":"2407.21422","title":"Revisiting Tampered Scene Text Detection in the Era of Generative AI","created":"2024-07-31","cited_by_count":21},{"id":"2312.06934","title":"Toward Real Text Manipulation Detection: New Dataset and New Solution","created":"2023-12-12","cited_by_count":20}],"next_cursor":null}