{"list":"other","total":56,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"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":"1409.1556","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","created":"2014-09-04","cited_by_count":15364},{"id":"1910.10683","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","created":"2019-10-23","cited_by_count":14599},{"id":"2005.12872","title":"End-to-End Object Detection with Transformers","created":"2020-05-26","cited_by_count":7414},{"id":"1905.11946","title":"EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks","created":"2019-05-28","cited_by_count":6442},{"id":"2012.12877","title":"Training data-efficient image transformers & distillation through attention","created":"2020-12-23","cited_by_count":4586},{"id":"2010.04159","title":"Deformable DETR: Deformable Transformers for End-to-End Object Detection","created":"2020-10-08","cited_by_count":3422},{"id":"1705.07750","title":"Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset","created":"2017-05-22","cited_by_count":3270},{"id":"1610.02357","title":"Xception: Deep Learning with Depthwise Separable Convolutions","created":"2016-10-07","cited_by_count":2332},{"id":"1905.02244","title":"Searching for MobileNetV3","created":"2019-05-06","cited_by_count":1994},{"id":"1901.08971","title":"FaceForensics++: Learning to Detect Manipulated Facial Images","created":"2019-01-25","cited_by_count":1101},{"id":"1709.02371","title":"PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume","created":"2017-09-07","cited_by_count":968},{"id":"1912.11035","title":"CNN-generated images are surprisingly easy to spot... for now","created":"2019-12-23","cited_by_count":847},{"id":"1706.08612","title":"VoxCeleb: a large-scale speaker identification dataset","created":"2017-06-26","cited_by_count":732},{"id":"2003.00196","title":"First Order Motion Model for Image Animation","created":"2020-02-29","cited_by_count":704},{"id":"2007.14808","title":"Face2Face: Real-time Face Capture and Reenactment of RGB Videos","created":"2020-07-29","cited_by_count":632},{"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":"1912.13458","title":"Face X-ray for More General Face Forgery Detection","created":"2019-12-31","cited_by_count":470},{"id":"2004.08955","title":"ResNeSt: Split-Attention Networks","created":"2020-04-19","cited_by_count":445},{"id":"1809.00888","title":"MesoNet: a Compact Facial Video Forgery Detection Network","created":"2018-09-04","cited_by_count":409},{"id":"1711.10305","title":"Learning Spatio-Temporal Representation with Pseudo-3D Residual Networks","created":"2017-11-28","cited_by_count":387},{"id":"2103.02406","title":"Multi-attentional Deepfake Detection","created":"2021-03-03","cited_by_count":341},{"id":"1908.05932","title":"FSGAN: Subject Agnostic Face Swapping and Reenactment","created":"2019-08-16","cited_by_count":320},{"id":"1811.00656","title":"Exposing DeepFake Videos By Detecting Face Warping Artifacts","created":"2018-11-01","cited_by_count":319},{"id":"1811.00661","title":"Exposing Deep Fakes Using Inconsistent Head Poses","created":"2018-11-01","cited_by_count":297},{"id":"1904.12356","title":"Deferred Neural Rendering: Image Synthesis using Neural Textures","created":"2019-04-28","cited_by_count":253},{"id":"1912.13457","title":"FaceShifter: Towards High Fidelity And Occlusion Aware Face Swapping","created":"2019-12-31","cited_by_count":221},{"id":"2002.00133","title":"Global Texture Enhancement for Fake Face Detection in the Wild","created":"2020-02-01","cited_by_count":220},{"id":"1812.08685","title":"DeepFakes: a New Threat to Face Recognition? Assessment and Detection","created":"2018-12-20","cited_by_count":209},{"id":"2101.01456","title":"WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection","created":"2021-01-05","cited_by_count":209},{"id":"1901.00212","title":"EdgeConnect: Generative Image Inpainting with Adversarial Edge Learning","created":"2019-01-01","cited_by_count":163},{"id":"1703.07814","title":"R-C3D: Region Convolutional 3D Network for Temporal Activity Detection","created":"2017-03-22","cited_by_count":161},{"id":"1807.09251","title":"GANimation: Anatomically-aware Facial Animation from a Single Image","created":"2018-07-24","cited_by_count":161},{"id":"2008.03412","title":"Two-branch Recurrent Network for Isolating Deepfakes in Videos","created":"2020-08-08","cited_by_count":161},{"id":"1911.13239","title":"DoveNet: Deep Image Harmonization via Domain Verification","created":"2019-11-27","cited_by_count":135},{"id":"1906.06876","title":"Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos","created":"2019-06-17","cited_by_count":130},{"id":"2103.05630","title":"ForgeryNet: A Versatile Benchmark for Comprehensive Forgery Analysis","created":"2021-03-09","cited_by_count":126},{"id":"1803.11276","title":"Two-Stream Neural Networks for Tampered Face Detection","created":"2018-03-29","cited_by_count":125},{"id":"1703.09211","title":"Coherent Online Video Style Transfer","created":"2017-03-27","cited_by_count":96},{"id":"1807.11079","title":"ReenactGAN: Learning to Reenact Faces via Boundary Transfer","created":"2018-07-29","cited_by_count":85},{"id":"2102.11126","title":"Deepfake Video Detection Using Convolutional Vision Transformer","created":"2021-02-22","cited_by_count":79},{"id":"1911.00686","title":"Unmasking DeepFakes with simple Features","created":"2019-11-02","cited_by_count":78},{"id":"2010.11838","title":"Blind Video Temporal Consistency via Deep Video Prior","created":"2020-10-22","cited_by_count":76},{"id":"1910.12467","title":"Use of a Capsule Network to Detect Fake Images and Videos","created":"2019-10-28","cited_by_count":63},{"id":"1703.04615","title":"Recasting Residual-based Local Descriptors as Convolutional Neural Networks: an Application to Image Forgery Detection","created":"2017-03-14","cited_by_count":56},{"id":"1604.08610","title":"Artistic style transfer for videos","created":"2016-04-28","cited_by_count":55},{"id":"1804.03447","title":"RSGAN: Face Swapping and Editing using Face and Hair Representation in Latent Spaces","created":"2018-04-10","cited_by_count":50},{"id":"1904.01909","title":"ICface: Interpretable and Controllable Face Reenactment Using GANs","created":"2019-04-03","cited_by_count":50},{"id":"2005.10954","title":"Head2Head: Video-based Neural Head Synthesis","created":"2020-05-22","cited_by_count":40},{"id":"2001.01265","title":"FDFtNet: Facing Off Fake Images using Fake Detection Fine-tuning Network","created":"2020-01-05","cited_by_count":19},{"id":"1911.11394","title":"LaFIn: Generative Landmark Guided Face Inpainting","created":"2019-11-26","cited_by_count":12},{"id":"2002.03723","title":"Deep Frequent Spatial Temporal Learning for Face Anti-Spoofing","created":"2020-01-20","cited_by_count":4}],"next_cursor":null}