{"list":"other","total":52,"rows":[{"id":"2103.00020","title":"Learning Transferable Visual Models From Natural Language Supervision","created":"2021-02-26","cited_by_count":33744},{"id":"2002.05709","title":"A Simple Framework for Contrastive Learning of Visual Representations","created":"2020-02-13","cited_by_count":12049},{"id":"1801.03924","title":"The Unreasonable Effectiveness of Deep Features as a Perceptual Metric","created":"2018-01-11","cited_by_count":11177},{"id":"1911.05722","title":"Momentum Contrast for Unsupervised Visual Representation Learning","created":"2019-11-13","cited_by_count":7513},{"id":"1812.04948","title":"A Style-Based Generator Architecture for Generative Adversarial Networks","created":"2018-12-12","cited_by_count":6013},{"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":"1809.11096","title":"Large Scale GAN Training for High Fidelity Natural Image Synthesis","created":"2018-09-28","cited_by_count":2626},{"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":"2112.07945","title":"Efficient Geometry-aware 3D Generative Adversarial Networks","created":"2021-12-15","cited_by_count":1205},{"id":"2006.06676","title":"Training Generative Adversarial Networks with Limited Data","created":"2020-06-11","cited_by_count":1186},{"id":"1805.08318","title":"Self-Attention Generative Adversarial Networks","created":"2018-05-21","cited_by_count":809},{"id":"1802.03601","title":"Deep Visual Domain Adaptation: A Survey","created":"2018-02-10","cited_by_count":635},{"id":"2102.02766","title":"Designing an Encoder for StyleGAN Image Manipulation","created":"2021-02-04","cited_by_count":544},{"id":"2202.00273","title":"StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets","created":"2022-02-01","cited_by_count":492},{"id":"2005.09635","title":"InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANs","created":"2020-05-18","cited_by_count":394},{"id":"2006.10738","title":"Differentiable Augmentation for Data-Efficient GAN Training","created":"2020-06-18","cited_by_count":363},{"id":"2011.12799","title":"StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation","created":"2020-11-25","cited_by_count":332},{"id":"2104.06820","title":"Few-shot Image Generation via Cross-domain Correspondence","created":"2021-04-13","cited_by_count":207},{"id":"1611.05644","title":"Inverting The Generator Of A Generative Adversarial Network","created":"2016-11-17","cited_by_count":140},{"id":"1805.01677","title":"Transferring GANs: generating images from limited data","created":"2018-05-04","cited_by_count":134},{"id":"2002.10964","title":"Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs","created":"2020-02-25","cited_by_count":132},{"id":"2012.02780","title":"Few-shot Image Generation with Elastic Weight Consolidation","created":"2020-12-04","cited_by_count":122},{"id":"2206.10207","title":"SemMAE: Semantic-Guided Masking for Learning Masked Autoencoders","created":"2022-06-21","cited_by_count":114},{"id":"2104.03310","title":"Regularizing Generative Adversarial Networks under Limited Data","created":"2021-04-07","cited_by_count":107},{"id":"1912.05270","title":"MineGAN: effective knowledge transfer from GANs to target domains with few images","created":"2019-12-11","cited_by_count":106},{"id":"1904.01774","title":"Image Generation From Small Datasets via Batch Statistics Adaptation","created":"2019-04-03","cited_by_count":102},{"id":"2012.14176","title":"Deep Visual Domain Adaptation","created":"2020-12-28","cited_by_count":91},{"id":"2006.02595","title":"Image Augmentations for GAN Training","created":"2020-06-04","cited_by_count":78},{"id":"2002.04724","title":"Improved Consistency Regularization for GANs","created":"2020-02-11","cited_by_count":69},{"id":"2110.08398","title":"Mind the Gap: Domain Gap Control for Single Shot Domain Adaptation for Generative Adversarial Networks","created":"2021-10-15","cited_by_count":68},{"id":"2010.11943","title":"Few-Shot Adaptation of Generative Adversarial Networks","created":"2020-10-22","cited_by_count":64},{"id":"2106.04566","title":"Data-Efficient Instance Generation from Instance Discrimination","created":"2021-06-08","cited_by_count":58},{"id":"2203.04121","title":"Few Shot Generative Model Adaption via Relaxed Spatial Structural Alignment","created":"2022-03-06","cited_by_count":54},{"id":"2111.06849","title":"Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data","created":"2021-11-12","cited_by_count":53},{"id":"2112.11641","title":"JoJoGAN: One Shot Face Stylization","created":"2021-12-22","cited_by_count":49},{"id":"2205.03805","title":"A Closer Look at Few-shot Image Generation","created":"2022-05-08","cited_by_count":49},{"id":"2103.09742","title":"Training GANs with Stronger Augmentations via Contrastive Discriminator","created":"2021-03-17","cited_by_count":45},{"id":"2110.07288","title":"View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums","created":"2021-10-14","cited_by_count":45},{"id":"2111.09876","title":"One-Shot Generative Domain Adaptation","created":"2021-11-18","cited_by_count":41},{"id":"2110.12427","title":"Image-Based CLIP-Guided Essence Transfer","created":"2021-10-24","cited_by_count":39},{"id":"2210.16559","title":"Few-shot Image Generation via Adaptation-Aware Kernel Modulation","created":"2022-10-29","cited_by_count":33},{"id":"2008.08930","title":"A Systematic Survey of Regularization and Normalization in GANs","created":"2020-08-19","cited_by_count":27},{"id":"2207.08736","title":"Towards Diverse and Faithful One-shot Adaption of Generative Adversarial Networks","created":"2022-07-18","cited_by_count":23},{"id":"2204.08329","title":"A Comprehensive Survey on Data-Efficient GANs in Image Generation","created":"2022-04-18","cited_by_count":20},{"id":"2210.08884","title":"HyperDomainNet: Universal Domain Adaptation for Generative Adversarial Networks","created":"2022-10-17","cited_by_count":19},{"id":"2202.08506","title":"CSCNet: Contextual Semantic Consistency Network for Trajectory Prediction in Crowded Spaces","created":"2022-02-17","cited_by_count":18},{"id":"2207.08630","title":"FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANs","created":"2022-07-18","cited_by_count":17},{"id":"2211.14554","title":"DynaGAN: Dynamic Few-shot Adaptation of GANs to Multiple Domains","created":"2022-11-26","cited_by_count":15},{"id":"2301.05225","title":"Domain Expansion of Image Generators","created":"2023-01-12","cited_by_count":13},{"id":"2008.09041","title":"A New Perspective on Stabilizing GANs training: Direct Adversarial Training","created":"2020-08-19","cited_by_count":12},{"id":"2210.15194","title":"Few-shot Image Generation via Masked Discrimination","created":"2022-10-27","cited_by_count":12}],"next_cursor":null}