{"list":"other","total":51,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1812.04948","title":"A Style-Based Generator Architecture for Generative Adversarial Networks","created":"2018-12-12","cited_by_count":6013},{"id":"2203.00667","title":"Generative Adversarial Networks","created":"2022-03-01","cited_by_count":5627},{"id":"1411.7766","title":"Deep Learning Face Attributes in the Wild","created":"2014-11-28","cited_by_count":3693},{"id":"1912.04958","title":"Analyzing and Improving the Image Quality of StyleGAN","created":"2019-12-03","cited_by_count":3588},{"id":"1710.10196","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","created":"2017-10-27","cited_by_count":2988},{"id":"1511.06434","title":"Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks","created":"2015-11-19","cited_by_count":2054},{"id":"1802.05957","title":"Spectral Normalization for Generative Adversarial Networks","created":"2018-02-16","cited_by_count":1636},{"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":"2106.12423","title":"Alias-Free Generative Adversarial Networks","created":"2021-06-23","cited_by_count":1184},{"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":"1703.05921","title":"Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery","created":"2017-03-17","cited_by_count":566},{"id":"1802.04633","title":"Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring","created":"2018-02-13","cited_by_count":357},{"id":"2112.14683","title":"StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2","created":"2021-12-29","cited_by_count":301},{"id":"1701.04082","title":"Embedding Watermarks into Deep Neural Networks","created":"2017-01-15","cited_by_count":248},{"id":"1711.10678","title":"AttGAN: Facial Attribute Editing by Only Changing What You Want","created":"2017-11-29","cited_by_count":242},{"id":"1802.03446","title":"Pros and Cons of GAN Evaluation Measures","created":"2018-02-09","cited_by_count":224},{"id":"2007.08457","title":"Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Data","created":"2020-07-16","cited_by_count":201},{"id":"2109.06590","title":"High-Fidelity GAN Inversion for Image Attribute Editing","created":"2021-09-14","cited_by_count":197},{"id":"2010.05903","title":"PANDA: Adapting Pretrained Features for Anomaly Detection and Segmentation","created":"2020-10-12","cited_by_count":175},{"id":"2002.12200","title":"Entangled Watermarks as a Defense against Model Extraction","created":"2020-02-27","cited_by_count":149},{"id":"1904.09709","title":"STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing","created":"2019-04-22","cited_by_count":120},{"id":"1711.01894","title":"Adversarial Frontier Stitching for Remote Neural Network Watermarking","created":"2017-11-06","cited_by_count":118},{"id":"2302.03251","title":"SCALE-UP: An Efficient Black-box Input-level Backdoor Detection via Analyzing Scaled Prediction Consistency","created":"2023-02-07","cited_by_count":97},{"id":"1912.00888","title":"Deep Neural Network Fingerprinting by Conferrable Adversarial Examples","created":"2019-12-02","cited_by_count":93},{"id":"2012.08726","title":"Responsible Disclosure of Generative Models Using Scalable Fingerprinting","created":"2020-12-16","cited_by_count":91},{"id":"1909.07830","title":"[Extended version] Rethinking Deep Neural Network Ownership Verification: Embedding Passports to Defeat Ambiguity Attacks","created":"2019-09-16","cited_by_count":88},{"id":"2210.00875","title":"Untargeted Backdoor Watermark: Towards Harmless and Stealthy Dataset Copyright Protection","created":"2022-09-27","cited_by_count":86},{"id":"1801.05365","title":"Learning Deep Features for One-Class Classification","created":"2018-01-16","cited_by_count":76},{"id":"1910.12903","title":"IPGuard: Protecting Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary","created":"2019-10-28","cited_by_count":70},{"id":"2108.04974","title":"SoK: How Robust is Image Classification Deep Neural Network Watermarking? (Extended Version)","created":"2021-08-11","cited_by_count":69},{"id":"2105.04580","title":"Towards Discovery and Attribution of Open-world GAN Generated Images","created":"2021-05-10","cited_by_count":66},{"id":"2209.06015","title":"Black-box Dataset Ownership Verification via Backdoor Watermarking","created":"2022-08-04","cited_by_count":65},{"id":"2202.08602","title":"Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations","created":"2022-02-17","cited_by_count":61},{"id":"2106.07873","title":"Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images","created":"2021-06-15","cited_by_count":58},{"id":"2002.11088","title":"Model Watermarking for Image Processing Networks","created":"2020-02-25","cited_by_count":56},{"id":"2103.00218","title":"Countering Malicious DeepFakes: Survey, Battleground, and Horizon","created":"2021-02-27","cited_by_count":56},{"id":"2103.03243","title":"Anycost GANs for Interactive Image Synthesis and Editing","created":"2021-03-04","cited_by_count":54},{"id":"2103.04980","title":"Deep Model Intellectual Property Protection via Deep Watermarking","created":"2021-03-08","cited_by_count":54},{"id":"2202.13843","title":"Deepfake Network Architecture Attribution","created":"2022-02-28","cited_by_count":47},{"id":"2102.04362","title":"Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack","created":"2021-02-08","cited_by_count":46},{"id":"2207.07972","title":"Certified Neural Network Watermarks with Randomized Smoothing","created":"2022-07-16","cited_by_count":41},{"id":"2207.02063","title":"RepMix: Representation Mixing for Robust Attribution of Synthesized Images","created":"2022-07-05","cited_by_count":39},{"id":"2210.15127","title":"Rethinking the Reverse-engineering of Trojan Triggers","created":"2022-10-27","cited_by_count":39},{"id":"1905.02259","title":"Source Generator Attribution via Inversion","created":"2019-05-06","cited_by_count":22},{"id":"2009.08697","title":"Fine-tuning Is Not Enough: A Simple yet Effective Watermark Removal Attack for DNN Models","created":"2020-09-18","cited_by_count":21},{"id":"1612.00686","title":"Identifying and Categorizing Anomalies in Retinal Imaging Data","created":"2016-12-02","cited_by_count":18},{"id":"2001.08873","title":"Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification","created":"2020-01-24","cited_by_count":17},{"id":"2210.07809","title":"Free Fine-tuning: A Plug-and-Play Watermarking Scheme for Deep Neural Networks","created":"2022-10-14","cited_by_count":15},{"id":"2204.04513","title":"On the Exploitation of Deepfake Model Recognition","created":"2022-04-09","cited_by_count":14},{"id":"1903.01931","title":"O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks","created":"2019-03-05","cited_by_count":4}],"next_cursor":null}