{"list":"other","total":69,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1412.6572","title":"Explaining and Harnessing Adversarial Examples","created":"2014-12-20","cited_by_count":7364},{"id":"1312.6199","title":"Intriguing properties of neural networks","created":"2013-12-21","cited_by_count":5155},{"id":"1709.01507","title":"Squeeze-and-Excitation Networks","created":"2017-09-05","cited_by_count":4789},{"id":"1710.10196","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","created":"2017-10-27","cited_by_count":2988},{"id":"1503.03832","title":"FaceNet: A Unified Embedding for Face Recognition and Clustering","created":"2015-03-12","cited_by_count":2849},{"id":"1801.09414","title":"CosFace: Large Margin Cosine Loss for Deep Face Recognition","created":"2018-01-29","cited_by_count":971},{"id":"1803.06978","title":"Improving Transferability of Adversarial Examples with Input Diversity","created":"2018-03-19","cited_by_count":599},{"id":"2002.10857","title":"Circle Loss: A Unified Perspective of Pair Similarity Optimization","created":"2020-02-25","cited_by_count":403},{"id":"1908.06281","title":"Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks","created":"2019-08-17","cited_by_count":355},{"id":"2103.06627","title":"MagFace: A Universal Representation for Face Recognition and Quality Assessment","created":"2021-03-11","cited_by_count":334},{"id":"2004.00288","title":"CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition","created":"2020-04-01","cited_by_count":321},{"id":"1804.06655","title":"Deep Face Recognition: A Survey","created":"2018-04-18","cited_by_count":276},{"id":"2307.14539","title":"Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models","created":"2023-07-26","cited_by_count":273},{"id":"2103.15571","title":"Enhancing the Transferability of Adversarial Attacks through Variance Tuning","created":"2021-03-29","cited_by_count":244},{"id":"2302.04578","title":"Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples","created":"2023-02-09","cited_by_count":167},{"id":"2010.05222","title":"Partial FC: Training 10 Million Identities on a Single Machine","created":"2020-10-11","cited_by_count":163},{"id":"1911.10692","title":"Mitigate Bias in Face Recognition using Skewness-Aware Reinforcement Learning","created":"2019-11-25","cited_by_count":145},{"id":"2206.09391","title":"Towards Adversarial Attack on Vision-Language Pre-training Models","created":"2022-06-19","cited_by_count":144},{"id":"2207.05382","title":"Frequency Domain Model Augmentation for Adversarial Attack","created":"2022-07-12","cited_by_count":130},{"id":"1912.11188","title":"Adversarial AutoAugment","created":"2019-12-24","cited_by_count":111},{"id":"2307.14061","title":"Set-level Guidance Attack: Boosting Adversarial Transferability of Vision-Language Pre-training Models","created":"2023-07-26","cited_by_count":108},{"id":"2308.07026","title":"AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning","created":"2023-08-14","cited_by_count":103},{"id":"2105.03162","title":"Adv-Makeup: A New Imperceptible and Transferable Attack on Face Recognition","created":"2021-05-07","cited_by_count":97},{"id":"2101.07922","title":"LowKey: Leveraging Adversarial Attacks to Protect Social Media Users from Facial Recognition","created":"2021-01-20","cited_by_count":94},{"id":"1906.07927","title":"SemanticAdv: Generating Adversarial Examples via Attribute-conditional Image Editing","created":"2019-06-19","cited_by_count":93},{"id":"2004.05790","title":"Towards Transferable Adversarial Attack against Deep Face Recognition","created":"2020-04-13","cited_by_count":80},{"id":"2106.15058","title":"Improving Transferability of Adversarial Patches on Face Recognition with Generative Models","created":"2021-06-29","cited_by_count":80},{"id":"2203.03121","title":"Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer","created":"2022-03-07","cited_by_count":78},{"id":"2305.10665","title":"Content-based Unrestricted Adversarial Attack","created":"2023-05-18","cited_by_count":73},{"id":"2308.04995","title":"IDiff-Face: Synthetic-based Face Recognition through Fizzy Identity-Conditioned Diffusion Models","created":"2023-08-09","cited_by_count":72},{"id":"2308.10299","title":"Boosting Adversarial Transferability by Block Shuffle and Rotation","created":"2023-08-20","cited_by_count":64},{"id":"2003.06814","title":"Towards Face Encryption by Generating Adversarial Identity Masks","created":"2020-03-15","cited_by_count":63},{"id":"2309.14700","title":"Structure Invariant Transformation for better Adversarial Transferability","created":"2023-09-26","cited_by_count":62},{"id":"1912.00833","title":"Mis-classified Vector Guided Softmax Loss for Face Recognition","created":"2019-11-26","cited_by_count":60},{"id":"2205.06548","title":"Meta Balanced Network for Fair Face Recognition","created":"2022-05-13","cited_by_count":53},{"id":"2101.04407","title":"FaceX-Zoo: A PyTorch Toolbox for Face Recognition","created":"2021-01-12","cited_by_count":49},{"id":"2210.06871","title":"Adv-Attribute: Inconspicuous and Transferable Adversarial Attack on Face Recognition","created":"2022-10-13","cited_by_count":43},{"id":"2306.10008","title":"CLIP2Protect: Protecting Facial Privacy using Text-Guided Makeup via Adversarial Latent Search","created":"2023-06-16","cited_by_count":43},{"id":"2304.05640","title":"Instance-Aware Domain Generalization for Face Anti-Spoofing","created":"2023-04-12","cited_by_count":42},{"id":"2308.02897","title":"An Adaptive Model Ensemble Adversarial Attack for Boosting Adversarial Transferability","created":"2023-08-05","cited_by_count":42},{"id":"1809.08352","title":"Unrestricted Adversarial Examples","created":"2018-09-22","cited_by_count":40},{"id":"2207.13129","title":"LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity","created":"2022-07-26","cited_by_count":39},{"id":"2303.13868","title":"Physically Adversarial Infrared Patches with Learnable Shapes and Locations","created":"2023-03-24","cited_by_count":39},{"id":"2210.02041","title":"Natural Color Fool: Towards Boosting Black-box Unrestricted Attacks","created":"2022-10-05","cited_by_count":38},{"id":"2202.12513","title":"TeachAugment: Data Augmentation Optimization Using Teacher Knowledge","created":"2022-02-25","cited_by_count":37},{"id":"2303.12512","title":"Sibling-Attack: Rethinking Transferable Adversarial Attacks against Face Recognition","created":"2023-03-22","cited_by_count":34},{"id":"2207.10015","title":"Generative Domain Adaptation for Face Anti-Spoofing","created":"2022-07-20","cited_by_count":33},{"id":"2303.15818","title":"Towards Effective Adversarial Textured 3D Meshes on Physical Face Recognition","created":"2023-03-28","cited_by_count":33},{"id":"2405.09882","title":"DiffAM: Diffusion-based Adversarial Makeup Transfer for Facial Privacy Protection","created":"2024-05-16","cited_by_count":32},{"id":"2308.07009","title":"ACTIVE: Towards Highly Transferable 3D Physical Camouflage for Universal and Robust Vehicle Evasion","created":"2023-08-14","cited_by_count":31},{"id":"1909.09481","title":"Adversarial Learning with Margin-based Triplet Embedding Regularization","created":"2019-09-20","cited_by_count":29},{"id":"2207.09868","title":"Adaptive Mixture of Experts Learning for Generalizable Face Anti-Spoofing","created":"2022-07-20","cited_by_count":28},{"id":"2104.12378","title":"Delving into Data: Effectively Substitute Training for Black-box Attack","created":"2021-04-26","cited_by_count":27},{"id":"2307.07859","title":"Unified Adversarial Patch for Cross-modal Attacks in the Physical World","created":"2023-07-15","cited_by_count":27},{"id":"2102.09603","title":"Towards Solving the DeepFake Problem : An Analysis on Improving DeepFake Detection using Dynamic Face Augmentation","created":"2021-02-18","cited_by_count":25},{"id":"2205.13412","title":"Physical-World Optical Adversarial Attacks on 3D Face Recognition","created":"2022-05-26","cited_by_count":23},{"id":"2307.07653","title":"RFLA: A Stealthy Reflected Light Adversarial Attack in the Physical World","created":"2023-07-14","cited_by_count":23},{"id":"2308.06015","title":"Enhancing Generalization of Universal Adversarial Perturbation through Gradient Aggregation","created":"2023-08-11","cited_by_count":22},{"id":"2403.19334","title":"Test-Time Domain Generalization for Face Anti-Spoofing","created":"2024-03-28","cited_by_count":20},{"id":"2308.10601","title":"Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer","created":"2023-08-21","cited_by_count":13},{"id":"2007.10172","title":"NPCFace: Negative-Positive Collaborative Training for Large-scale Face Recognition","created":"2020-07-20","cited_by_count":9},{"id":"2301.12993","title":"Benchmarking Robustness to Adversarial Image Obfuscations","created":"2023-01-30","cited_by_count":8},{"id":"1812.00194","title":"Racial Faces in-the-Wild: Reducing Racial Bias by Information Maximization Adaptation Network","created":"2018-12-01","cited_by_count":7},{"id":"2204.00972","title":"DST: Dynamic Substitute Training for Data-free Black-box Attack","created":"2022-04-03","cited_by_count":7},{"id":"2210.16117","title":"Improving the Transferability of Adversarial Attacks on Face Recognition with Beneficial Perturbation Feature Augmentation","created":"2022-10-28","cited_by_count":7},{"id":"2309.01582","title":"Improving Visual Quality and Transferability of Adversarial Attacks on Face Recognition Simultaneously with Adversarial Restoration","created":"2023-09-04","cited_by_count":5},{"id":"2308.07625","title":"Backpropagation Path Search On Adversarial Transferability","created":"2023-08-15","cited_by_count":4},{"id":"2405.16940","title":"Adversarial Attacks on Both Face Recognition and Face Anti-spoofing Models","created":"2024-05-27","cited_by_count":4}],"next_cursor":null}