{"list":"other","total":124,"rows":[{"id":"1409.1556","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","created":"2014-09-04","cited_by_count":15364},{"id":"1409.0575","title":"ImageNet Large Scale Visual Recognition Challenge","created":"2014-09-01","cited_by_count":8498},{"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":"1611.07004","title":"Image-to-Image Translation with Conditional Adversarial Networks","created":"2016-11-21","cited_by_count":4527},{"id":"1312.6114","title":"Auto-Encoding Variational Bayes","created":"2013-12-20","cited_by_count":4053},{"id":"1710.10196","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","created":"2017-10-27","cited_by_count":2988},{"id":"1610.02357","title":"Xception: Deep Learning with Depthwise Separable Convolutions","created":"2016-10-07","cited_by_count":2332},{"id":"1901.08971","title":"FaceForensics++: Learning to Detect Manipulated Facial Images","created":"2019-01-25","cited_by_count":1101},{"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":"1906.02691","title":"An Introduction to Variational Autoencoders","created":"2019-06-06","cited_by_count":1000},{"id":"1606.05328","title":"Conditional Image Generation with PixelCNN Decoders","created":"2016-06-16","cited_by_count":862},{"id":"1601.06759","title":"Pixel Recurrent Neural Networks","created":"2016-01-25","cited_by_count":816},{"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":"2011.15126","title":"One-Shot Free-View Neural Talking-Head Synthesis for Video Conferencing","created":"2020-11-30","cited_by_count":444},{"id":"1809.00888","title":"MesoNet: a Compact Facial Video Forgery Detection Network","created":"2018-09-04","cited_by_count":409},{"id":"2103.02406","title":"Multi-attentional Deepfake Detection","created":"2021-03-03","cited_by_count":341},{"id":"2204.08376","title":"Detecting Deepfakes with Self-Blended Images","created":"2022-04-18","cited_by_count":338},{"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":"1711.11586","title":"Toward Multimodal Image-to-Image Translation","created":"2017-11-30","cited_by_count":296},{"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":"1910.01717","title":"On the Detection of Digital Face Manipulation","created":"2019-10-03","cited_by_count":260},{"id":"2001.03024","title":"DeeperForensics-1.0: A Large-Scale Dataset for Real-World Face Forgery Detection","created":"2020-01-09","cited_by_count":254},{"id":"2004.11138","title":"The Creation and Detection of Deepfakes: A Survey","created":"2020-04-23","cited_by_count":247},{"id":"2103.01856","title":"Spatial-Phase Shallow Learning: Rethinking Face Forgery Detection in Frequency Domain","created":"2021-03-02","cited_by_count":244},{"id":"2106.06340","title":"SimSwap: An Efficient Framework For High Fidelity Face Swapping","created":"2021-06-11","cited_by_count":243},{"id":"1711.10678","title":"AttGAN: Facial Attribute Editing by Only Changing What You Want","created":"2017-11-29","cited_by_count":242},{"id":"2001.00179","title":"DeepFakes and Beyond: A Survey of Face Manipulation and Fake Detection","created":"2020-01-01","cited_by_count":233},{"id":"1812.08685","title":"DeepFakes: a New Threat to Face Recognition? Assessment and Detection","created":"2018-12-20","cited_by_count":209},{"id":"1910.08854","title":"The Deepfake Detection Challenge (DFDC) Preview Dataset","created":"2019-10-19","cited_by_count":209},{"id":"2001.06564","title":"Media Forensics and DeepFakes: an overview","created":"2020-01-18","cited_by_count":209},{"id":"2108.05080","title":"FakeAVCeleb: A Novel Audio-Video Multimodal Deepfake Dataset","created":"2021-08-11","cited_by_count":181},{"id":"1810.11215","title":"Capsule-Forensics: Using Capsule Networks to Detect Forged Images and Videos","created":"2018-10-26","cited_by_count":180},{"id":"2012.09311","title":"Learning Self-Consistency for Deepfake Detection","created":"2020-12-16","cited_by_count":179},{"id":"2003.04092","title":"Searching Central Difference Convolutional Networks for Face Anti-Spoofing","created":"2020-03-09","cited_by_count":173},{"id":"1803.11097","title":"Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision","created":"2018-03-29","cited_by_count":167},{"id":"1908.08705","title":"AdvHat: Real-world adversarial attack on ArcFace Face ID system","created":"2019-08-23","cited_by_count":163},{"id":"2008.03412","title":"Two-branch Recurrent Network for Isolating Deepfakes in Videos","created":"2020-08-08","cited_by_count":161},{"id":"2108.06693","title":"Exploring Temporal Coherence for More General Video Face Forgery Detection","created":"2021-08-15","cited_by_count":159},{"id":"1901.02212","title":"FakeCatcher: Detection of Synthetic Portrait Videos using Biological Signals","created":"2019-01-08","cited_by_count":145},{"id":"2004.14043","title":"Single-Side Domain Generalization for Face Anti-Spoofing","created":"2020-04-29","cited_by_count":139},{"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":"2201.07131","title":"Leveraging Real Talking Faces via Self-Supervision for Robust Forgery Detection","created":"2022-01-18","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":"1905.00582","title":"Recurrent Convolutional Strategies for Face Manipulation Detection in Videos","created":"2019-05-02","cited_by_count":118},{"id":"2003.06711","title":"Emotions Don't Lie: An Audio-Visual Deepfake Detection Method Using Affective Cues","created":"2020-03-14","cited_by_count":111},{"id":"2007.12342","title":"CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotations","created":"2020-07-24","cited_by_count":109},{"id":"2011.02062","title":"NAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofing","created":"2020-11-03","cited_by_count":105},{"id":"2105.04932","title":"One Shot Face Swapping on Megapixels","created":"2021-05-11","cited_by_count":105},{"id":"2105.02577","title":"Local Relation Learning for Face Forgery Detection","created":"2021-05-06","cited_by_count":100},{"id":"2112.13522","title":"Dual Contrastive Learning for General Face Forgery Detection","created":"2021-12-27","cited_by_count":100},{"id":"2105.03162","title":"Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition","created":"2021-05-07","cited_by_count":97},{"id":"2004.01959","title":"Cross-domain Face Presentation Attack Detection via Multi-domain Disentangled Representation Learning","created":"2020-04-04","cited_by_count":93},{"id":"1911.08139","title":"MarioNETte: Few-shot Face Reenactment Preserving Identity of Unseen Targets","created":"2019-11-19","cited_by_count":90},{"id":"2108.07938","title":"FACIAL: Synthesizing Dynamic Talking Face with Implicit Attribute Learning","created":"2021-08-18","cited_by_count":90},{"id":"2109.01860","title":"Spatiotemporal Inconsistency Learning for DeepFake Video Detection","created":"2021-09-04","cited_by_count":88},{"id":"1907.11921","title":"Remote Heart Rate Measurement from Highly Compressed Facial Videos: an End-to-end Deep Learning Solution with Video Enhancement","created":"2019-07-27","cited_by_count":87},{"id":"2103.16076","title":"Face Forensics in the Wild","created":"2021-03-30","cited_by_count":87},{"id":"1911.10771","title":"Regularized Fine-grained Meta Face Anti-spoofing","created":"2019-11-25","cited_by_count":86},{"id":"1801.00349","title":"A General Framework for Adversarial Examples with Objectives","created":"2017-12-31","cited_by_count":84},{"id":"1511.06316","title":"face anti-spoofing based on color texture analysis","created":"2015-11-19","cited_by_count":82},{"id":"1408.5601","title":"Learn Convolutional Neural Network for Face Anti-Spoofing","created":"2014-08-24","cited_by_count":80},{"id":"2103.10094","title":"KoDF: A Large-scale Korean DeepFake Detection Dataset","created":"2021-03-18","cited_by_count":80},{"id":"1907.04047","title":"Deep Pixel-wise Binary Supervision for Face Presentation Attack Detection","created":"2019-07-09","cited_by_count":76},{"id":"1904.02860","title":"Deep Tree Learning for Zero-shot Face Anti-Spoofing","created":"2019-04-05","cited_by_count":73},{"id":"2003.08061","title":"Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing","created":"2020-03-18","cited_by_count":70},{"id":"2203.14325","title":"PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognition","created":"2022-03-27","cited_by_count":67},{"id":"2002.12749","title":"Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples","created":"2020-02-09","cited_by_count":66},{"id":"2006.07634","title":"DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms","created":"2020-06-13","cited_by_count":65},{"id":"2008.08250","title":"Face Anti-Spoofing Via Disentangled Representation Learning","created":"2020-08-19","cited_by_count":65},{"id":"2106.14948","title":"Deep Learning for Face Anti-Spoofing: A Survey","created":"2021-06-28","cited_by_count":65},{"id":"2007.02157","title":"Face Anti-Spoofing with Human Material Perception","created":"2020-07-04","cited_by_count":62},{"id":"2007.09273","title":"On Disentangling Spoof Trace for Generic Face Anti-Spoofing","created":"2020-07-17","cited_by_count":62},{"id":"2104.04480","title":"Improving the Efficiency and Robustness of Deepfakes Detection through Precise Geometric Features","created":"2021-04-09","cited_by_count":57},{"id":"2008.12262","title":"DeepFake Detection Based on the Discrepancy Between the Face and its Context","created":"2020-08-27","cited_by_count":56},{"id":"2103.00218","title":"Countering Malicious DeepFakes: Survey, Battleground, and Horizon","created":"2021-02-27","cited_by_count":56},{"id":"2008.04585","title":"Sharp Multiple Instance Learning for DeepFake Video Detection","created":"2020-08-11","cited_by_count":55},{"id":"2011.09737","title":"Face Forgery Detection by 3D Decomposition","created":"2020-11-19","cited_by_count":53},{"id":"1904.01909","title":"ICface: Interpretable and Controllable Face Reenactment Using GANs","created":"2019-04-03","cited_by_count":50},{"id":"2102.12129","title":"Self-Domain Adaptation for Face Anti-Spoofing","created":"2021-02-24","cited_by_count":49},{"id":"2108.02667","title":"Adaptive Normalized Representation Learning for Generalizable Face Anti-Spoofing","created":"2021-08-05","cited_by_count":49},{"id":"2011.09957","title":"Adversarial Threats to DeepFake Detection: A Practical Perspective","created":"2020-11-19","cited_by_count":48},{"id":"2105.02453","title":"Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing","created":"2021-05-06","cited_by_count":46},{"id":"2011.12032","title":"Revisiting Pixel-Wise Supervision for Face Anti-Spoofing","created":"2020-11-24","cited_by_count":45},{"id":"2203.04564","title":"Region-Aware Face Swapping","created":"2022-03-09","cited_by_count":45},{"id":"2203.15674","title":"Exploring Frequency Adversarial Attacks for Face Forgery Detection","created":"2022-03-29","cited_by_count":45},{"id":"1904.12490","title":"Learning Meta Model for Zero- and Few-shot Face Anti-spoofing","created":"2019-04-29","cited_by_count":44},{"id":"2003.09234","title":"DeepFake Detection: Current Challenges and Next Steps","created":"2020-03-11","cited_by_count":44},{"id":"2011.08019","title":"On the Effectiveness of Vision Transformers for Zero-shot Face Anti-Spoofing","created":"2020-11-16","cited_by_count":44},{"id":"2104.06148","title":"Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detection","created":"2021-04-13","cited_by_count":43},{"id":"2103.00948","title":"Cross Modal Focal Loss for RGBD Face Anti-Spoofing","created":"2021-03-01","cited_by_count":41},{"id":"2104.07419","title":"TransRPPG: Remote Photoplethysmography Transformer for 3D Mask Face Presentation Attack Detection","created":"2021-04-15","cited_by_count":41},{"id":"2001.09598","title":"FakeLocator: Robust Localization of GAN-Based Face Manipulations","created":"2020-01-27","cited_by_count":40},{"id":"2107.05821","title":"Detect and Locate: Exposing Face Manipulation by Semantic- and Noise-level Telltales","created":"2021-07-13","cited_by_count":39}],"next_cursor":"100"}