{"list":"other","total":51,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"id":"2010.11929","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","created":"2020-10-22","cited_by_count":30186},{"id":"2103.14030","title":"Swin Transformer: Hierarchical Vision Transformer using Shifted Windows","created":"2021-03-25","cited_by_count":12139},{"id":"1710.09412","title":"mixup: Beyond Empirical Risk Minimization","created":"2017-10-25","cited_by_count":5183},{"id":"2012.12877","title":"Training data-efficient image transformers & distillation through attention","created":"2020-12-23","cited_by_count":4586},{"id":"1503.03832","title":"FaceNet: A Unified Embedding for Face Recognition and Clustering","created":"2015-03-12","cited_by_count":2849},{"id":"1909.13719","title":"RandAugment: Practical automated data augmentation with a reduced search space","created":"2019-09-30","cited_by_count":2269},{"id":"1905.02244","title":"Searching for MobileNetV3","created":"2019-05-06","cited_by_count":1994},{"id":"2102.12122","title":"Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions","created":"2021-02-24","cited_by_count":1962},{"id":"1506.02025","title":"Spatial Transformer Networks","created":"2015-06-05","cited_by_count":1429},{"id":"2101.11986","title":"Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet","created":"2021-01-28","cited_by_count":1101},{"id":"1801.09414","title":"CosFace: Large Margin Cosine Loss for Deep Face Recognition","created":"2018-01-29","cited_by_count":971},{"id":"2103.15808","title":"CvT: Introducing Convolutions to Vision Transformers","created":"2021-03-29","cited_by_count":947},{"id":"1710.08092","title":"VGGFace2: A dataset for recognising faces across pose and age","created":"2017-10-23","cited_by_count":914},{"id":"2103.17239","title":"Going deeper with Image Transformers","created":"2021-03-31","cited_by_count":764},{"id":"1704.08063","title":"SphereFace: Deep Hypersphere Embedding for Face Recognition","created":"2017-04-26","cited_by_count":737},{"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":"2106.10270","title":"How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers","created":"2021-06-18","cited_by_count":569},{"id":"1703.07332","title":"How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)","created":"2017-03-21","cited_by_count":525},{"id":"2104.01136","title":"LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference","created":"2021-04-02","cited_by_count":475},{"id":"1411.7923","title":"Learning Face Representation from Scratch","created":"2014-11-28","cited_by_count":453},{"id":"2002.10857","title":"Circle Loss: A Unified Perspective of Pair Similarity Optimization","created":"2020-02-25","cited_by_count":403},{"id":"2106.14881","title":"Early Convolutions Help Transformers See Better","created":"2021-06-28","cited_by_count":396},{"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":"1612.02295","title":"Large-Margin Softmax Loss for Convolutional Neural Networks","created":"2016-12-07","cited_by_count":296},{"id":"2103.11816","title":"Incorporating Convolution Designs into Visual Transformers","created":"2021-03-22","cited_by_count":248},{"id":"1605.07648","title":"FractalNet: Ultra-Deep Neural Networks without Residuals","created":"2016-05-24","cited_by_count":216},{"id":"1512.00596","title":"The MegaFace Benchmark: 1 Million Faces for Recognition at Scale","created":"2015-12-02","cited_by_count":200},{"id":"2010.05222","title":"Partial FC: Training 10 Million Identities on a Single Machine","created":"2020-10-11","cited_by_count":163},{"id":"2104.12533","title":"Visformer: The Vision-friendly Transformer","created":"2021-04-26","cited_by_count":137},{"id":"2003.11339","title":"Data Uncertainty Learning in Face Recognition","created":"2020-03-25","cited_by_count":134},{"id":"1806.07823","title":"Unsupervised Learning of Object Landmarks through Conditional Image Generation","created":"2018-06-20","cited_by_count":114},{"id":"1603.01249","title":"HyperFace: A Deep Multi-task Learning Framework for Face Detection, Landmark Localization, Pose Estimation, and Gender Recognition","created":"2016-03-03","cited_by_count":104},{"id":"1804.04412","title":"Unsupervised Discovery of Object Landmarks as Structural Representations","created":"2018-04-12","cited_by_count":73},{"id":"1705.02193","title":"Unsupervised learning of object landmarks by factorized spatial embeddings","created":"2017-05-05","cited_by_count":64},{"id":"1806.06503","title":"Deforming Autoencoders: Unsupervised Disentangling of Shape and Appearance","created":"2018-06-18","cited_by_count":58},{"id":"2103.14803","title":"Face Transformer for Recognition","created":"2021-03-27","cited_by_count":46},{"id":"2108.01513","title":"SphereFace2: Binary Classification is All You Need for Deep Face Recognition","created":"2021-08-03","cited_by_count":42},{"id":"2108.08191","title":"Masked Face Recognition Challenge: The InsightFace Track Report","created":"2021-08-18","cited_by_count":41},{"id":"2005.10497","title":"GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition","created":"2020-05-21","cited_by_count":38},{"id":"1408.3967","title":"Learning Deep Representation for Face Alignment with Auxiliary Attributes","created":"2014-08-18","cited_by_count":32},{"id":"2008.06674","title":"BroadFace: Looking at Tens of Thousands of People at Once for Face Recognition","created":"2020-08-15","cited_by_count":30},{"id":"1904.11960","title":"Lifting AutoEncoders: Unsupervised Learning of a Fully-Disentangled 3D Morphable Model using Deep Non-Rigid Structure from Motion","created":"2019-04-26","cited_by_count":23},{"id":"1506.07310","title":"Targeting Ultimate Accuracy: Face Recognition via Deep Embedding","created":"2015-06-24","cited_by_count":18},{"id":"1607.05427","title":"Trunk-Branch Ensemble Convolutional Neural Networks for Video-based Face Recognition","created":"2016-07-19","cited_by_count":16},{"id":"1807.11440","title":"Comparator Networks","created":"2018-07-30","cited_by_count":13},{"id":"1808.04976","title":"Pairwise Relational Networks for Face Recognition","created":"2018-08-15","cited_by_count":11},{"id":"1910.09469","title":"Object landmark discovery through unsupervised adaptation","created":"2019-10-21","cited_by_count":8}],"next_cursor":null}