{"list":"other","total":64,"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":"1412.6980","title":"Adam: A Method for Stochastic Optimization","created":"2014-12-22","cited_by_count":37240},{"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":"1505.04597","title":"U-Net: Convolutional Networks for Biomedical Image Segmentation","created":"2015-05-18","cited_by_count":19713},{"id":"2005.12872","title":"End-to-End Object Detection with Transformers","created":"2020-05-26","cited_by_count":7414},{"id":"2111.06377","title":"Masked Autoencoders Are Scalable Vision Learners","created":"2021-11-11","cited_by_count":7403},{"id":"1706.04599","title":"On Calibration of Modern Neural Networks","created":"2017-06-14","cited_by_count":4960},{"id":"2012.12877","title":"Training data-efficient image transformers & distillation through attention","created":"2020-12-23","cited_by_count":4586},{"id":"1411.7766","title":"Deep Learning Face Attributes in the Wild","created":"2014-11-28","cited_by_count":3693},{"id":"2010.04159","title":"Deformable DETR: Deformable Transformers for End-to-End Object Detection","created":"2020-10-08","cited_by_count":3422},{"id":"2001.07685","title":"FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence","created":"2020-01-21","cited_by_count":2085},{"id":"1908.07919","title":"Deep High-Resolution Representation Learning for Visual Recognition","created":"2019-08-20","cited_by_count":1420},{"id":"1905.02249","title":"MixMatch: A Holistic Approach to Semi-Supervised Learning","created":"2019-05-06","cited_by_count":1391},{"id":"1911.04252","title":"Self-training with Noisy Student improves ImageNet classification","created":"2019-11-11","cited_by_count":1311},{"id":"1610.02242","title":"Temporal Ensembling for Semi-Supervised Learning","created":"2016-10-07","cited_by_count":1057},{"id":"1704.03976","title":"Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning","created":"2017-04-13","cited_by_count":920},{"id":"1603.06937","title":"Stacked Hourglass Networks for Human Pose Estimation","created":"2016-03-22","cited_by_count":915},{"id":"1812.05159","title":"An Empirical Study of Example Forgetting during Deep Neural Network Learning","created":"2018-12-12","cited_by_count":678},{"id":"2110.08263","title":"FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling","created":"2021-10-15","cited_by_count":540},{"id":"1908.02983","title":"Pseudo-Labeling and Confirmation Bias in Deep Semi-Supervised Learning","created":"2019-08-08","cited_by_count":510},{"id":"1804.06208","title":"Simple Baselines for Human Pose Estimation and Tracking","created":"2018-04-17","cited_by_count":502},{"id":"2103.10697","title":"ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases","created":"2021-03-19","cited_by_count":484},{"id":"1606.04586","title":"Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning","created":"2016-06-14","cited_by_count":441},{"id":"2106.07998","title":"Revisiting the Calibration of Modern Neural Networks","created":"2021-06-15","cited_by_count":390},{"id":"2006.06882","title":"Rethinking Pre-training and Self-training","created":"2020-06-11","cited_by_count":352},{"id":"2102.09480","title":"Unbiased Teacher for Semi-Supervised Object Detection","created":"2021-02-18","cited_by_count":306},{"id":"1911.03584","title":"On the Relationship between Self-Attention and Convolutional Layers","created":"2019-11-08","cited_by_count":300},{"id":"1511.06523","title":"WIDER FACE: A Face Detection Benchmark","created":"2015-11-20","cited_by_count":298},{"id":"2005.04757","title":"A Simple Semi-Supervised Learning Framework for Object Detection","created":"2020-05-10","cited_by_count":282},{"id":"2106.05095","title":"ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation","created":"2021-06-09","cited_by_count":184},{"id":"1805.10483","title":"Look at Boundary: A Boundary-Aware Face Alignment Algorithm","created":"2018-05-26","cited_by_count":138},{"id":"1904.07399","title":"Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression","created":"2019-04-16","cited_by_count":128},{"id":"1712.04440","title":"Data Distillation: Towards Omni-Supervised Learning","created":"2017-12-12","cited_by_count":126},{"id":"2103.03571","title":"Cycle Self-Training for Domain Adaptation","created":"2021-03-05","cited_by_count":120},{"id":"2103.11402","title":"Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework","created":"2021-03-21","cited_by_count":113},{"id":"1711.06753","title":"Wing Loss for Robust Facial Landmark Localisation with Convolutional Neural Networks","created":"2017-11-17","cited_by_count":109},{"id":"2004.02980","title":"LUVLi Face Alignment: Estimating Landmarks' Location, Uncertainty, and Visibility Likelihood","created":"2020-04-06","cited_by_count":87},{"id":"2104.07256","title":"A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation","created":"2021-04-15","cited_by_count":79},{"id":"1908.00748","title":"Integrating Spatial Configuration into Heatmap Regression Based CNNs for Landmark Localization","created":"2019-08-02","cited_by_count":77},{"id":"2003.03771","title":"Pixel-in-Pixel Net: Towards Efficient Facial Landmark Detection in the Wild","created":"2020-03-08","cited_by_count":74},{"id":"2012.15175","title":"Rethinking the Heatmap Regression for Bottom-up Human Pose Estimation","created":"2020-12-30","cited_by_count":69},{"id":"2202.07136","title":"Debiased Self-Training for Semi-Supervised Learning","created":"2022-02-15","cited_by_count":62},{"id":"2004.08190","title":"Structured Landmark Detection via Topology-Adapting Deep Graph Learning","created":"2020-04-17","cited_by_count":50},{"id":"2203.06541","title":"Sparse Local Patch Transformer for Robust Face Alignment and Landmarks Inherent Relation Learning","created":"2022-03-13","cited_by_count":47},{"id":"1904.02549","title":"DeCaFA: Deep Convolutional Cascade for Face Alignment In The Wild","created":"2019-04-04","cited_by_count":46},{"id":"2106.00168","title":"Rethinking Pseudo Labels for Semi-Supervised Object Detection","created":"2021-06-01","cited_by_count":45},{"id":"1709.01591","title":"Improving Landmark Localization with Semi-Supervised Learning","created":"2017-09-05","cited_by_count":39},{"id":"1908.06440","title":"Aggregation via Separation: Boosting Facial Landmark Detector with Semi-Supervised Style Translation","created":"2019-08-18","cited_by_count":33},{"id":"1911.10448","title":"3FabRec: Fast Few-shot Face alignment by Reconstruction","created":"2019-11-24","cited_by_count":33},{"id":"1908.08841","title":"Cephalometric Landmark Detection by AttentiveFeature Pyramid Fusion and Regression-Voting","created":"2019-08-23","cited_by_count":32},{"id":"2208.10808","title":"Towards Accurate Facial Landmark Detection via Cascaded Transformers","created":"2022-08-23","cited_by_count":31},{"id":"2103.04657","title":"You Only Learn Once: Universal Anatomical Landmark Detection","created":"2021-03-08","cited_by_count":29},{"id":"1908.02116","title":"Teacher Supervises Students How to Learn From Partially Labeled Images for Facial Landmark Detection","created":"2019-08-06","cited_by_count":28},{"id":"1906.07549","title":"An Attention-Guided Deep Regression Model for Landmark Detection in Cephalograms","created":"2019-06-17","cited_by_count":27},{"id":"2011.12498","title":"An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation","created":"2020-11-25","cited_by_count":21},{"id":"1903.10661","title":"Semantic Alignment: Finding Semantically Consistent Ground-truth for Facial Landmark Detection","created":"2019-03-26","cited_by_count":16},{"id":"1903.11633","title":"Laplace Landmark Localization","created":"2019-03-27","cited_by_count":16},{"id":"2303.07840","title":"Precise Facial Landmark Detection by Reference Heatmap Transformer","created":"2023-03-14","cited_by_count":16},{"id":"2201.08613","title":"Pseudo-Labeled Auto-Curriculum Learning for Semi-Supervised Keypoint Localization","created":"2022-01-21","cited_by_count":14},{"id":"2207.03917","title":"RePFormer: Refinement Pyramid Transformer for Robust Facial Landmark Detection","created":"2022-07-08","cited_by_count":13},{"id":"2311.09965","title":"SurgPLAN: Surgical Phase Localization Network for Phase Recognition","created":"2023-11-16","cited_by_count":12},{"id":"2308.13286","title":"Unsupervised Domain Adaptation for Anatomical Landmark Detection","created":"2023-08-25","cited_by_count":5},{"id":"2105.13150","title":"When Liebig's Barrel Meets Facial Landmark Detection: A Practical Model","created":"2021-05-27","cited_by_count":3}],"next_cursor":null}