{"list":"other","total":54,"rows":[{"id":"2006.11239","title":"Denoising Diffusion Probabilistic Models","created":"2020-06-19","cited_by_count":21076},{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"1812.04948","title":"A Style-Based Generator Architecture for Generative Adversarial Networks","created":"2018-12-12","cited_by_count":6013},{"id":"2102.09672","title":"Improved Denoising Diffusion Probabilistic Models","created":"2021-02-18","cited_by_count":3761},{"id":"1912.04958","title":"Analyzing and Improving the Image Quality of StyleGAN","created":"2019-12-03","cited_by_count":3588},{"id":"2208.12242","title":"DreamBooth: Fine Tuning Text-to-Image Diffusion Models for Subject-Driven Generation","created":"2022-08-25","cited_by_count":3300},{"id":"2112.07945","title":"Efficient Geometry-aware 3D Generative Adversarial Networks","created":"2021-12-15","cited_by_count":1205},{"id":"2106.12423","title":"Alias-Free Generative Adversarial Networks","created":"2021-06-23","cited_by_count":1184},{"id":"2301.13188","title":"Extracting Training Data from Diffusion Models","created":"2023-01-30","cited_by_count":732},{"id":"1904.03189","title":"Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?","created":"2019-04-05","cited_by_count":675},{"id":"1607.08221","title":"MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition","created":"2016-07-27","cited_by_count":624},{"id":"1710.07035","title":"Generative Adversarial Networks: An Overview","created":"2017-10-19","cited_by_count":590},{"id":"1903.08527","title":"Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set","created":"2019-03-20","cited_by_count":482},{"id":"1411.7923","title":"Learning Face Representation from Scratch","created":"2014-11-28","cited_by_count":453},{"id":"2111.15640","title":"Diffusion Autoencoders: Toward a Meaningful and Decodable Representation","created":"2021-11-30","cited_by_count":449},{"id":"2106.05744","title":"Pivotal Tuning for Latent-based Editing of Real Images","created":"2021-06-10","cited_by_count":427},{"id":"2212.03860","title":"Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models","created":"2022-12-07","cited_by_count":424},{"id":"2004.00049","title":"In-Domain GAN Inversion for Real Image Editing","created":"2020-03-31","cited_by_count":420},{"id":"2204.00964","title":"AdaFace: Quality Adaptive Margin for Face Recognition","created":"2022-04-03","cited_by_count":391},{"id":"1708.08197","title":"Cross-Age LFW: A Database for Studying Cross-Age Face Recognition in Unconstrained Environments","created":"2017-08-28","cited_by_count":260},{"id":"2103.04098","title":"WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition","created":"2021-03-06","cited_by_count":223},{"id":"2004.11660","title":"Disentangled and Controllable Face Image Generation via 3D Imitative-Contrastive Learning","created":"2020-04-24","cited_by_count":220},{"id":"2305.10973","title":"Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold","created":"2023-05-18","cited_by_count":219},{"id":"2305.20086","title":"Understanding and Mitigating Copying in Diffusion Models","created":"2023-05-31","cited_by_count":209},{"id":"2109.15102","title":"Fake It Till You Make It: Face analysis in the wild using synthetic data alone","created":"2021-09-30","cited_by_count":200},{"id":"1709.08398","title":"Morphable Face Models - An Open Framework","created":"2017-09-25","cited_by_count":138},{"id":"2206.08343","title":"Realistic One-shot Mesh-based Head Avatars","created":"2022-06-16","cited_by_count":119},{"id":"2304.07060","title":"DCFace: Synthetic Face Generation with Dual Condition Diffusion Model","created":"2023-04-14","cited_by_count":116},{"id":"2108.07960","title":"SynFace: Face Recognition with Synthetic Data","created":"2021-08-18","cited_by_count":106},{"id":"2302.10870","title":"On Provable Copyright Protection for Generative Models","created":"2023-02-21","cited_by_count":98},{"id":"2004.03458","title":"Learning Formation of Physically-Based Face Attributes","created":"2020-04-02","cited_by_count":94},{"id":"2003.02488","title":"Demographic Bias in Biometrics: A Survey on an Emerging Challenge","created":"2020-03-05","cited_by_count":93},{"id":"2210.02579","title":"DigiFace-1M: 1 Million Digital Face Images for Face Recognition","created":"2022-10-05","cited_by_count":92},{"id":"2101.02477","title":"GAN-Control: Explicitly Controllable GANs","created":"2021-01-07","cited_by_count":91},{"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":"2304.05097","title":"One-Shot High-Fidelity Talking-Head Synthesis with Deformable Neural Radiance Field","created":"2023-04-11","cited_by_count":68},{"id":"2206.10520","title":"SFace: Privacy-friendly and Accurate Face Recognition using Synthetic Data","created":"2022-06-21","cited_by_count":63},{"id":"1809.09349","title":"The jamming transition as a paradigm to understand the loss landscape of deep neural networks","created":"2018-09-25","cited_by_count":62},{"id":"2305.19962","title":"GANDiffFace: Controllable Generation of Synthetic Datasets for Face Recognition with Realistic Variations","created":"2023-05-31","cited_by_count":49},{"id":"2211.13874","title":"FFHQ-UV: Normalized Facial UV-Texture Dataset for 3D Face Reconstruction","created":"2022-11-25","cited_by_count":39},{"id":"2305.09641","title":"FitMe: Deep Photorealistic 3D Morphable Model Avatars","created":"2023-05-16","cited_by_count":38},{"id":"2404.04580","title":"SDFR: Synthetic Data for Face Recognition Competition","created":"2024-04-06","cited_by_count":28},{"id":"2305.00358","title":"Identity-driven Three-Player Generative Adversarial Network for Synthetic-based Face Recognition","created":"2023-04-30","cited_by_count":27},{"id":"2106.04215","title":"On the use of automatically generated synthetic image datasets for benchmarking face recognition","created":"2021-06-08","cited_by_count":26},{"id":"2308.05441","title":"Benchmarking Algorithmic Bias in Face Recognition: An Experimental Approach Using Synthetic Faces and Human Evaluation","created":"2023-08-10","cited_by_count":25},{"id":"2302.08509","title":"3D-aware Conditional Image Synthesis","created":"2023-02-16","cited_by_count":24},{"id":"1812.09916","title":"Improving MMD-GAN Training with Repulsive Loss Function","created":"2018-12-24","cited_by_count":22},{"id":"2307.05151","title":"ExFaceGAN: Exploring Identity Directions in GAN's Learned Latent Space for Synthetic Identity Generation","created":"2023-07-11","cited_by_count":22},{"id":"2305.16150","title":"Unifying GANs and Score-Based Diffusion as Generative Particle Models","created":"2023-05-25","cited_by_count":21},{"id":"1708.08819","title":"Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields","created":"2017-08-29","cited_by_count":20},{"id":"2403.09450","title":"Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk","created":"2024-03-14","cited_by_count":17},{"id":"2202.11833","title":"Near Perfect GAN Inversion","created":"2022-02-23","cited_by_count":15},{"id":"2103.00233","title":"Learning with Smooth Hinge Losses","created":"2021-02-27","cited_by_count":9},{"id":"2205.06102","title":"Tensor-based Emotion Editing in the StyleGAN Latent Space","created":"2022-05-12","cited_by_count":7}],"next_cursor":null}