{"list":"other","total":55,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"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":"1503.02531","title":"Distilling the Knowledge in a Neural Network","created":"2015-03-09","cited_by_count":10324},{"id":"2005.12872","title":"End-to-End Object Detection with Transformers","created":"2020-05-26","cited_by_count":7414},{"id":"2010.04159","title":"Deformable DETR: Deformable Transformers for End-to-End Object Detection","created":"2020-10-08","cited_by_count":3422},{"id":"1804.02767","title":"YOLOv3: An Incremental Improvement","created":"2018-04-08","cited_by_count":2659},{"id":"2006.05525","title":"Knowledge Distillation: A Survey","created":"2020-06-09","cited_by_count":1603},{"id":"2102.04306","title":"TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation","created":"2021-02-08","cited_by_count":1558},{"id":"2103.15808","title":"CvT: Introducing Convolutions to Vision Transformers","created":"2021-03-29","cited_by_count":947},{"id":"1904.05068","title":"Relational Knowledge Distillation","created":"2019-04-10","cited_by_count":889},{"id":"1802.05751","title":"Image Transformer","created":"2018-02-15","cited_by_count":772},{"id":"2111.14819","title":"Point-BERT: Pre-training 3D Point Cloud Transformers with Masked Point Modeling","created":"2021-11-29","cited_by_count":653},{"id":"1801.04264","title":"Real-world Anomaly Detection in Surveillance Videos","created":"2018-01-12","cited_by_count":577},{"id":"1904.02639","title":"Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection","created":"2019-04-04","cited_by_count":564},{"id":"1312.6184","title":"Do Deep Nets Really Need to be Deep?","created":"2013-12-21","cited_by_count":474},{"id":"1712.09867","title":"Future Frame Prediction for Anomaly Detection -- A New Baseline","created":"2017-12-28","cited_by_count":391},{"id":"1911.02357","title":"Uninformed Students: Student-Teacher Anomaly Detection with Discriminative Latent Embeddings","created":"2019-11-06","cited_by_count":386},{"id":"2011.11108","title":"Multiresolution Knowledge Distillation for Anomaly Detection","created":"2020-11-22","cited_by_count":285},{"id":"2003.13228","title":"Learning Memory-guided Normality for Anomaly Detection","created":"2020-03-30","cited_by_count":278},{"id":"1604.04574","title":"Learning Temporal Regularity in Video Sequences","created":"2016-04-15","cited_by_count":254},{"id":"1903.07256","title":"Graph Convolutional Label Noise Cleaner: Train a Plug-and-play Action Classifier for Anomaly Detection","created":"2019-03-18","cited_by_count":171},{"id":"2007.02500","title":"Deep Learning for Anomaly Detection: A Review","created":"2020-07-06","cited_by_count":159},{"id":"2011.07491","title":"Anomaly Detection in Video via Self-Supervised and Multi-Task Learning","created":"2020-11-15","cited_by_count":148},{"id":"2108.06852","title":"A Hybrid Video Anomaly Detection Framework via Memory-Augmented Flow Reconstruction and Flow-Guided Frame Prediction","created":"2021-08-16","cited_by_count":129},{"id":"2111.09099","title":"Self-Supervised Predictive Convolutional Attentive Block for Anomaly Detection","created":"2021-11-17","cited_by_count":119},{"id":"1908.06351","title":"Anomaly Detection in Video Sequence with Appearance-Motion Correspondence","created":"2019-08-17","cited_by_count":118},{"id":"1812.04960","title":"Object-centric Auto-encoders and Dummy Anomalies for Abnormal Event Detection in Video","created":"2018-12-11","cited_by_count":111},{"id":"2203.03962","title":"Generative Cooperative Learning for Unsupervised Video Anomaly Detection","created":"2022-03-08","cited_by_count":102},{"id":"1902.05872","title":"Street Scene: A new dataset and evaluation protocol for video anomaly detection","created":"2019-02-15","cited_by_count":90},{"id":"2004.05993","title":"A Survey of Single-Scene Video Anomaly Detection","created":"2020-04-13","cited_by_count":88},{"id":"2008.12328","title":"A Background-Agnostic Framework with Adversarial Training for Abnormal Event Detection in Video","created":"2020-08-27","cited_by_count":86},{"id":"2003.06780","title":"Self-trained Deep Ordinal Regression for End-to-End Video Anomaly Detection","created":"2020-03-15","cited_by_count":83},{"id":"1708.09644","title":"Abnormal Event Detection in Videos using Generative Adversarial Nets","created":"2017-08-31","cited_by_count":82},{"id":"2008.11988","title":"Cloze Test Helps: Effective Video Anomaly Detection via Learning to Complete Video Events","created":"2020-08-27","cited_by_count":70},{"id":"2002.01775","title":"Feature-map-level Online Adversarial Knowledge Distillation","created":"2020-02-05","cited_by_count":62},{"id":"2207.10172","title":"Video Anomaly Detection by Solving Decoupled Spatio-Temporal Jigsaw Puzzles","created":"2022-07-20","cited_by_count":62},{"id":"1709.09121","title":"Joint Detection and Recounting of Abnormal Events by Learning Deep Generic Knowledge","created":"2017-09-26","cited_by_count":55},{"id":"1609.00866","title":"Deep-Anomaly: Fully Convolutional Neural Network for Fast Anomaly Detection in Crowded Scenes","created":"2016-09-03","cited_by_count":50},{"id":"1705.08182","title":"Unmasking the abnormal events in video","created":"2017-05-23","cited_by_count":48},{"id":"1904.03624","title":"Learning Metrics from Teachers: Compact Networks for Image Embedding","created":"2019-04-07","cited_by_count":39},{"id":"2004.02072","title":"Any-Shot Sequential Anomaly Detection in Surveillance Videos","created":"2020-04-05","cited_by_count":34},{"id":"2209.12148","title":"Self-Supervised Masked Convolutional Transformer Block for Anomaly Detection","created":"2022-09-25","cited_by_count":34},{"id":"1610.00307","title":"Plug-and-Play CNN for Crowd Motion Analysis: An Application in Abnormal Event Detection","created":"2016-10-02","cited_by_count":32},{"id":"2001.09189","title":"Learning a distance function with a Siamese network to localize anomalies in videos","created":"2020-01-24","cited_by_count":31},{"id":"2110.09742","title":"Learning Not to Reconstruct Anomalies","created":"2021-10-19","cited_by_count":31},{"id":"1801.05030","title":"Detecting abnormal events in video using Narrowed Normality Clusters","created":"2018-01-12","cited_by_count":30},{"id":"2110.09768","title":"Synthetic Temporal Anomaly Guided End-to-End Video Anomaly Detection","created":"2021-10-19","cited_by_count":26},{"id":"1609.08938","title":"A Discriminative Framework for Anomaly Detection in Large Videos","created":"2016-09-28","cited_by_count":25},{"id":"1905.04457","title":"Triplet Distillation for Deep Face Recognition","created":"2019-05-11","cited_by_count":17},{"id":"2106.08613","title":"FastAno: Fast Anomaly Detection via Spatio-temporal Patch Transformation","created":"2021-06-16","cited_by_count":15},{"id":"2110.06400","title":"CyTran: A Cycle-Consistent Transformer with Multi-Level Consistency for Non-Contrast to Contrast CT Translation","created":"2021-10-12","cited_by_count":15},{"id":"2209.13363","title":"Anomaly Detection in Aerial Videos with Transformers","created":"2022-09-25","cited_by_count":11},{"id":"2011.05054","title":"Decoupled Appearance and Motion Learning for Efficient Anomaly Detection in Surveillance Video","created":"2020-11-10","cited_by_count":9},{"id":"2111.10561","title":"Teacher-Student Training and Triplet Loss to Reduce the Effect of Drastic Face Occlusion","created":"2021-11-20","cited_by_count":9}],"next_cursor":null}