{"list":"other","total":55,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1409.1556","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","created":"2014-09-04","cited_by_count":15364},{"id":"1905.11946","title":"EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks","created":"2019-05-28","cited_by_count":6442},{"id":"1512.00567","title":"Rethinking the Inception Architecture for Computer Vision","created":"2015-12-02","cited_by_count":5475},{"id":"1710.09412","title":"mixup: Beyond Empirical Risk Minimization","created":"2017-10-25","cited_by_count":5183},{"id":"1406.1078","title":"Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation","created":"2014-06-03","cited_by_count":4057},{"id":"1905.04899","title":"CutMix: Regularization Strategy to Train Strong Classifiers with Localizable Features","created":"2019-05-13","cited_by_count":2884},{"id":"1311.2524","title":"Rich feature hierarchies for accurate object detection and semantic segmentation","created":"2013-11-11","cited_by_count":2162},{"id":"1306.5151","title":"Fine-Grained Visual Classification of Aircraft","created":"2013-06-21","cited_by_count":1726},{"id":"1708.04552","title":"Improved Regularization of Convolutional Neural Networks with Cutout","created":"2017-08-15","cited_by_count":1628},{"id":"1506.02025","title":"Spatial Transformer Networks","created":"2015-06-05","cited_by_count":1429},{"id":"1805.07932","title":"Bilinear Attention Networks","created":"2018-05-21","cited_by_count":280},{"id":"1511.02274","title":"Stacked Attention Networks for Image Question Answering","created":"2015-11-07","cited_by_count":273},{"id":"1504.07889","title":"Bilinear CNNs for Fine-grained Visual Recognition","created":"2015-04-29","cited_by_count":228},{"id":"1511.02853","title":"Weakly Supervised Deep Detection Networks","created":"2015-11-09","cited_by_count":183},{"id":"1806.06193","title":"Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning","created":"2018-06-16","cited_by_count":174},{"id":"1804.06962","title":"Adversarial Complementary Learning for Weakly Supervised Object Localization","created":"2018-04-19","cited_by_count":166},{"id":"1908.10028","title":"Attention-based Dropout Layer for Weakly Supervised Object Localization","created":"2019-08-27","cited_by_count":125},{"id":"2108.08728","title":"Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification","created":"2021-08-19","cited_by_count":114},{"id":"1407.3867","title":"Part-based R-CNNs for Fine-grained Category Detection","created":"2014-07-15","cited_by_count":109},{"id":"1903.06150","title":"Looking for the Devil in the Details: Learning Trilinear Attention Sampling Network for Fine-grained Image Recognition","created":"2019-03-14","cited_by_count":95},{"id":"2002.10191","title":"Learning Attentive Pairwise Interaction for Fine-Grained Classification","created":"2020-02-24","cited_by_count":84},{"id":"2205.02151","title":"Dual Cross-Attention Learning for Fine-Grained Visual Categorization and Object Re-Identification","created":"2022-05-04","cited_by_count":78},{"id":"2005.10411","title":"Interpretable and Accurate Fine-grained Recognition via Region Grouping","created":"2020-05-21","cited_by_count":75},{"id":"1807.08902","title":"Self-produced Guidance for Weakly-supervised Object Localization","created":"2018-07-24","cited_by_count":72},{"id":"1903.02827","title":"Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification from the Bottom Up","created":"2019-03-07","cited_by_count":66},{"id":"1809.05934","title":"Maximum-Entropy Fine-Grained Classification","created":"2018-09-16","cited_by_count":65},{"id":"2002.04264","title":"The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification","created":"2020-02-11","cited_by_count":64},{"id":"1806.05372","title":"Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition","created":"2018-06-14","cited_by_count":58},{"id":"1901.09891","title":"See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification","created":"2019-01-26","cited_by_count":56},{"id":"2012.04846","title":"SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data","created":"2020-12-09","cited_by_count":56},{"id":"2105.08913","title":"Multiple Meta-model Quantifying for Medical Visual Question Answering","created":"2021-05-19","cited_by_count":54},{"id":"2110.05754","title":"Deep Federated Learning for Autonomous Driving","created":"2021-10-12","cited_by_count":54},{"id":"1909.11378","title":"Attention Convolutional Binary Neural Tree for Fine-Grained Visual Categorization","created":"2019-09-25","cited_by_count":51},{"id":"1406.2952","title":"Bird Species Categorization Using Pose Normalized Deep Convolutional Nets","created":"2014-06-11","cited_by_count":50},{"id":"2003.05235","title":"Channel Interaction Networks for Fine-Grained Image Categorization","created":"2020-03-11","cited_by_count":47},{"id":"1604.04994","title":"Selective Convolutional Descriptor Aggregation for Fine-Grained Image Retrieval","created":"2016-04-18","cited_by_count":44},{"id":"1810.13125","title":"Compact Generalized Non-local Network","created":"2018-10-31","cited_by_count":36},{"id":"1707.06772","title":"Improved Bilinear Pooling with CNNs","created":"2017-07-21","cited_by_count":29},{"id":"1709.02476","title":"Fine-grained Recognition in the Wild: A Multi-Task Domain Adaptation Approach","created":"2017-09-07","cited_by_count":27},{"id":"2110.02526","title":"Coarse-to-Fine Reasoning for Visual Question Answering","created":"2021-10-06","cited_by_count":25},{"id":"1912.06842","title":"Fine-grained Recognition: Accounting for Subtle Differences between Similar Classes","created":"2019-12-14","cited_by_count":24},{"id":"1703.10332","title":"Dynamic Computational Time for Visual Attention","created":"2017-03-30","cited_by_count":23},{"id":"1708.02108","title":"Two-Phase Learning for Weakly Supervised Object Localization","created":"2017-08-07","cited_by_count":21},{"id":"2003.14142","title":"Look-into-Object: Self-supervised Structure Modeling for Object Recognition","created":"2020-03-31","cited_by_count":20},{"id":"2111.04129","title":"Global-Local Attention for Emotion Recognition","created":"2021-11-07","cited_by_count":20},{"id":"2203.03253","title":"Dynamic MLP for Fine-Grained Image Classification by Leveraging Geographical and Temporal Information","created":"2022-03-07","cited_by_count":15},{"id":"2104.06770","title":"Graph-based Person Signature for Person Re-Identifications","created":"2021-04-14","cited_by_count":14},{"id":"2110.01293","title":"Light-weight Deformable Registration using Adversarial Learning with Distilling Knowledge","created":"2021-10-04","cited_by_count":12},{"id":"1603.00489","title":"Weakly Supervised Localization using Deep Feature Maps","created":"2016-03-01","cited_by_count":7},{"id":"1911.07344","title":"ELoPE: Fine-Grained Visual Classification with Efficient Localization, Pooling and Embedding","created":"2019-11-17","cited_by_count":7},{"id":"2106.10587","title":"Exploring Vision Transformers for Fine-grained Classification","created":"2021-06-19","cited_by_count":7},{"id":"2108.04628","title":"Learning Canonical 3D Object Representation for Fine-Grained Recognition","created":"2021-08-10","cited_by_count":7},{"id":"2108.03434","title":"NASOA: Towards Faster Task-oriented Online Fine-tuning with a Zoo of Models","created":"2021-08-07","cited_by_count":6},{"id":"1605.01130","title":"Mining Discriminative Triplets of Patches for Fine-Grained Classification","created":"2016-05-04","cited_by_count":2}],"next_cursor":null}