{"total":150,"rows":[{"id":"2107.08430","title":"YOLOX: Exceeding YOLO Series in 2021","created":"2021-07-18","cited_by_count":1071,"area":null},{"id":"2207.02696","title":"YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors","created":"2022-07-06","cited_by_count":982,"area":null},{"id":"2211.12860","title":"DETRs with Collaborative Hybrid Assignments Training","created":"2022-11-22","cited_by_count":274,"area":null},{"id":"2108.07755","title":"TOOD: Task-aligned One-stage Object Detection","created":"2021-08-17","cited_by_count":218,"area":null},{"id":"2212.07784","title":"RTMDet: An Empirical Study of Designing Real-Time Object Detectors","created":"2022-12-14","cited_by_count":195,"area":null},{"id":"2103.14259","title":"OTA: Optimal Transport Assignment for Object Detection","created":"2021-03-26","cited_by_count":178,"area":null},{"id":"2108.00708","title":"Group Fisher Pruning for Practical Network Compression","created":"2021-08-02","cited_by_count":131,"area":null},{"id":"2103.07461","title":"Probabilistic two-stage detection","created":"2021-03-12","cited_by_count":130,"area":null},{"id":"2104.01318","title":"Efficient DETR: Improving End-to-End Object Detector with Dense Prior","created":"2021-04-03","cited_by_count":128,"area":null},{"id":"2207.14096","title":"Towards Large-Scale Small Object Detection: Survey and Benchmarks","created":"2022-07-28","cited_by_count":122,"area":null},{"id":"2103.09460","title":"You Only Look One-level Feature","created":"2021-03-17","cited_by_count":116,"area":null},{"id":"2105.11111","title":"Oriented RepPoints for Aerial Object Detection","created":"2021-05-24","cited_by_count":102,"area":null},{"id":"2207.13085","title":"Group DETR: Fast DETR Training with Group-Wise One-to-Many Assignment","created":"2022-07-26","cited_by_count":98,"area":null},{"id":"2107.00420","title":"CBNet: A Composite Backbone Network Architecture for Object Detection","created":"2021-07-01","cited_by_count":77,"area":null},{"id":"2303.12776","title":"Dense Distinct Query for End-to-End Object Detection","created":"2023-03-22","cited_by_count":77,"area":null},{"id":"2203.10593","title":"Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation","created":"2022-03-20","cited_by_count":68,"area":"distill"},{"id":"2103.17202","title":"GrooMeD-NMS: Grouped Mathematically Differentiable NMS for Monocular 3D Object Detection","created":"2021-03-31","cited_by_count":66,"area":null},{"id":"2101.08158","title":"Focal and Efficient IOU Loss for Accurate Bounding Box Regression","created":"2021-01-20","cited_by_count":57,"area":null},{"id":"2206.13996","title":"Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmark","created":"2022-06-28","cited_by_count":56,"area":null},{"id":"2102.12252","title":"Localization Distillation for Dense Object Detection","created":"2021-02-24","cited_by_count":55,"area":"distill"},{"id":"2110.13389","title":"A Normalized Gaussian Wasserstein Distance for Tiny Object Detection","created":"2021-10-26","cited_by_count":53,"area":null},{"id":"2208.08738","title":"RFLA: Gaussian Receptive Field based Label Assignment for Tiny Object Detection","created":"2022-08-18","cited_by_count":51,"area":null},{"id":"2201.02593","title":"Equalized Focal Loss for Dense Long-Tailed Object Detection","created":"2022-01-07","cited_by_count":46,"area":null},{"id":"2106.00168","title":"Rethinking Pseudo Labels for Semi-Supervised Object Detection","created":"2021-06-01","cited_by_count":45,"area":null},{"id":"2206.06608","title":"Label Matching Semi-Supervised Object Detection","created":"2022-06-14","cited_by_count":44,"area":null},{"id":"2209.01589","title":"Consistent-Teacher: Towards Reducing Inconsistent Pseudo-targets in Semi-supervised Object Detection","created":"2022-09-04","cited_by_count":43,"area":null},{"id":"2304.08876","title":"Dynamic Coarse-to-Fine Learning for Oriented Tiny Object Detection","created":"2023-04-18","cited_by_count":43,"area":null},{"id":"2107.02963","title":"Disentangle Your Dense Object Detector","created":"2021-07-07","cited_by_count":37,"area":null},{"id":"2101.10861","title":"A Review on Deep Learning in UAV Remote Sensing","created":"2021-01-22","cited_by_count":32,"area":null},{"id":"2204.07300","title":"Dense Learning based Semi-Supervised Object Detection","created":"2022-04-15","cited_by_count":32,"area":null},{"id":"2106.05681","title":"A Dataset And Benchmark Of Underwater Object Detection For Robot Picking","created":"2021-06-10","cited_by_count":31,"area":null},{"id":"2108.07482","title":"G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation","created":"2021-08-17","cited_by_count":28,"area":"distill"},{"id":"2203.09730","title":"A Dual Weighting Label Assignment Scheme for Object Detection","created":"2022-03-18","cited_by_count":26,"area":null},{"id":"2107.11669","title":"Rank & Sort Loss for Object Detection and Instance Segmentation","created":"2021-07-24","cited_by_count":22,"area":null},{"id":"2205.03688","title":"GenISP: Neural ISP for Low-Light Machine Cognition","created":"2022-05-07","cited_by_count":22,"area":null},{"id":"2306.04670","title":"Object Detection with Transformers: A Review","created":"2023-06-07","cited_by_count":22,"area":null},{"id":"2104.06936","title":"IQDet: Instance-wise Quality Distribution Sampling for Object Detection","created":"2021-04-14","cited_by_count":20,"area":null},{"id":"2205.11796","title":"G-Rep: Gaussian Representation for Arbitrary-Oriented Object Detection","created":"2022-05-24","cited_by_count":20,"area":null},{"id":"2204.05957","title":"Localization Distillation for Object Detection","created":"2022-04-12","cited_by_count":19,"area":"distill"},{"id":"2307.00934","title":"Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration","created":"2023-07-03","cited_by_count":19,"area":null},{"id":"2112.03549","title":"GaTector: A Unified Framework for Gaze Object Prediction","created":"2021-12-07","cited_by_count":18,"area":null},{"id":"2212.07593","title":"Enhanced Training of Query-Based Object Detection via Selective Query Recollection","created":"2022-12-15","cited_by_count":18,"area":null},{"id":"2108.10520","title":"Improving Object Detection by Label Assignment Distillation","created":"2021-08-24","cited_by_count":17,"area":null},{"id":"2302.07577","title":"Efficient Teacher: Semi-Supervised Object Detection for YOLOv5","created":"2023-02-15","cited_by_count":17,"area":null},{"id":"2309.14976","title":"MoCaE: Mixture of Calibrated Experts Significantly Improves Object Detection","created":"2023-09-26","cited_by_count":17,"area":"moe"},{"id":"2312.07352","title":"CholecTrack20: A Multi-Perspective Tracking Dataset for Surgical Tools","created":"2023-12-12","cited_by_count":17,"area":null},{"id":"2203.05469","title":"Prediction-Guided Distillation for Dense Object Detection","created":"2022-03-10","cited_by_count":14,"area":"distill"},{"id":"2303.12396","title":"Rigidity-Aware Detection for 6D Object Pose Estimation","created":"2023-03-22","cited_by_count":13,"area":null},{"id":"2303.17144","title":"DAMO-StreamNet: Optimizing Streaming Perception in Autonomous Driving","created":"2023-03-30","cited_by_count":13,"area":null},{"id":"2110.10364","title":"NOD: Taking a Closer Look at Detection under Extreme Low-Light Conditions with Night Object Detection Dataset","created":"2021-10-20","cited_by_count":12,"area":null},{"id":"2207.06985","title":"ObjectBox: From Centers to Boxes for Anchor-Free Object Detection","created":"2022-07-14","cited_by_count":12,"area":null},{"id":"2205.02101","title":"Dynamic Sparse R-CNN","created":"2022-05-04","cited_by_count":11,"area":null},{"id":"2405.20459","title":"On Calibration of Object Detectors: Pitfalls, Evaluation and Baselines","created":"2024-05-30","cited_by_count":11,"area":null},{"id":"2407.05909","title":"Multi-clue Consistency Learning to Bridge Gaps Between General and Oriented Object in Semi-supervised Detection","created":"2024-07-08","cited_by_count":11,"area":null},{"id":"2103.14027","title":"USB: Universal-Scale Object Detection Benchmark","created":"2021-03-25","cited_by_count":10,"area":null},{"id":"2109.05986","title":"Mutual Supervision for Dense Object Detection","created":"2021-09-13","cited_by_count":10,"area":null},{"id":"2111.07355","title":"Fracture Detection in Wrist X-ray Images Using Deep Learning-Based Object Detection Models","created":"2021-11-14","cited_by_count":10,"area":null},{"id":"2201.11620","title":"Domain generalization in deep learning-based mass detection in mammography: A large-scale multi-center study","created":"2022-01-27","cited_by_count":10,"area":null},{"id":"2206.13728","title":"Boosting R-CNN: Reweighting R-CNN Samples by RPN's Error for Underwater Object Detection","created":"2022-06-28","cited_by_count":10,"area":null},{"id":"2403.04309","title":"AO-DETR: Anti-Overlapping DETR for X-Ray Prohibited Items Detection","created":"2024-03-07","cited_by_count":9,"area":null},{"id":"2407.20078","title":"Background Semantics Matter: Cross-Task Feature Exchange Network for Clustered Infrared Small Target Detection","created":"2024-07-29","cited_by_count":9,"area":null},{"id":"2104.04899","title":"Location-Sensitive Visual Recognition with Cross-IOU Loss","created":"2021-04-11","cited_by_count":8,"area":null},{"id":"2210.05566","title":"The Equalization Losses: Gradient-Driven Training for Long-tailed Object Recognition","created":"2022-10-11","cited_by_count":8,"area":null},{"id":"2212.04067","title":"Consistency-Aware Anchor Pyramid Network for Crowd Localization","created":"2022-12-08","cited_by_count":8,"area":null},{"id":"2303.11567","title":"One-to-Few Label Assignment for End-to-End Dense Detection","created":"2023-03-21","cited_by_count":8,"area":null},{"id":"2304.04978","title":"StageInteractor: Query-based Object Detector with Cross-stage Interaction","created":"2023-04-11","cited_by_count":8,"area":null},{"id":"2406.02833","title":"DenoDet: Attention as Deformable Multi-Subspace Feature Denoising for Target Detection in SAR Images","created":"2024-06-05","cited_by_count":8,"area":null},{"id":"2101.04307","title":"LLA: Loss-aware Label Assignment for Dense Pedestrian Detection","created":"2021-01-12","cited_by_count":7,"area":null},{"id":"2303.01503","title":"FeatAug-DETR: Enriching One-to-Many Matching for DETRs with Feature Augmentation","created":"2023-03-02","cited_by_count":7,"area":null},{"id":"2408.16772","title":"An Effective Information Theoretic Framework for Channel Pruning","created":"2024-08-14","cited_by_count":7,"area":null},{"id":"2411.18296","title":"HUPE: Heuristic Underwater Perceptual Enhancement with Semantic Collaborative Learning","created":"2024-11-27","cited_by_count":7,"area":null},{"id":"2101.11782","title":"Object Detection Made Simpler by Eliminating Heuristic NMS","created":"2021-01-28","cited_by_count":6,"area":null},{"id":"2104.07303","title":"SiamCorners: Siamese Corner Networks for Visual Tracking","created":"2021-04-15","cited_by_count":6,"area":null},{"id":"2201.09396","title":"Dynamic Label Assignment for Object Detection by Combining Predicted IoUs and Anchor IoUs","created":"2022-01-23","cited_by_count":6,"area":null},{"id":"2310.16499","title":"Data Optimization in Deep Learning: A Survey","created":"2023-10-25","cited_by_count":6,"area":null},{"id":"2405.10148","title":"SpecDETR: A transformer-based hyperspectral point object detection network","created":"2024-05-16","cited_by_count":6,"area":null},{"id":"2110.09734","title":"Mask-aware IoU for Anchor Assignment in Real-time Instance Segmentation","created":"2021-10-19","cited_by_count":5,"area":null},{"id":"2208.00817","title":"DSLA: Dynamic smooth label assignment for efficient anchor-free object detection","created":"2022-08-01","cited_by_count":5,"area":null},{"id":"2304.07527","title":"Align-DETR: Enhancing End-to-end Object Detection with Aligned Loss","created":"2023-04-15","cited_by_count":5,"area":null},{"id":"2305.00675","title":"End-to-End Lane detection with One-to-Several Transformer","created":"2023-05-01","cited_by_count":5,"area":null},{"id":"2308.00931","title":"WaterFlow: Heuristic Normalizing Flow for Underwater Image Enhancement and Beyond","created":"2023-08-02","cited_by_count":5,"area":null},{"id":"2308.11918","title":"AMSP-UOD: When Vortex Convolution and Stochastic Perturbation Meet Underwater Object Detection","created":"2023-08-23","cited_by_count":5,"area":null},{"id":"2407.02394","title":"Similarity Distance-Based Label Assignment for Tiny Object Detection","created":"2024-07-02","cited_by_count":5,"area":null},{"id":"2407.19650","title":"Practical Video Object Detection via Feature Selection and Aggregation","created":"2024-07-29","cited_by_count":5,"area":null},{"id":"2110.12130","title":"RCNet: Reverse Feature Pyramid and Cross-scale Shift Network for Object Detection","created":"2021-10-23","cited_by_count":4,"area":null},{"id":"2206.01232","title":"What Are Expected Queries in End-to-End Object Detection?","created":"2022-06-02","cited_by_count":4,"area":null},{"id":"2207.12042","title":"Revisiting AP Loss for Dense Object Detection: Adaptive Ranking Pair Selection","created":"2022-07-25","cited_by_count":4,"area":null},{"id":"2301.01019","title":"Correlation Loss: Enforcing Correlation between Classification and Localization","created":"2023-01-03","cited_by_count":4,"area":null},{"id":"2308.05881","title":"Aphid Cluster Recognition and Detection in the Wild Using Deep Learning Models","created":"2023-08-10","cited_by_count":4,"area":null},{"id":"2312.10515","title":"PETDet: Proposal Enhancement for Two-Stage Fine-Grained Object Detection","created":"2023-12-16","cited_by_count":4,"area":null},{"id":"2404.13311","title":"STAT: Towards Generalizable Temporal Action Localization","created":"2024-04-20","cited_by_count":4,"area":null},{"id":"2103.09488","title":"Revisiting the Loss Weight Adjustment in Object Detection","created":"2021-03-17","cited_by_count":3,"area":null},{"id":"2202.00866","title":"Decoupled IoU Regression for Object Detection","created":"2022-02-02","cited_by_count":3,"area":null},{"id":"2209.10391","title":"IoU-Enhanced Attention for End-to-End Task Specific Object Detection","created":"2022-09-21","cited_by_count":3,"area":null},{"id":"2303.00284","title":"To Make Yourself Invisible with Adversarial Semantic Contours","created":"2023-03-01","cited_by_count":3,"area":null},{"id":"2303.01047","title":"Task-Specific Context Decoupling for Object Detection","created":"2023-03-02","cited_by_count":3,"area":null},{"id":"2307.05929","title":"A New Dataset and Comparative Study for Aphid Cluster Detection","created":"2023-07-12","cited_by_count":3,"area":null},{"id":"2307.13619","title":"RecursiveDet: End-to-End Region-based Recursive Object Detection","created":"2023-07-25","cited_by_count":3,"area":null},{"id":"2401.03749","title":"A Flying Bird Object Detection Method for Surveillance Video","created":"2024-01-08","cited_by_count":3,"area":null},{"id":"2405.04305","title":"A New Dataset and Comparative Study for Aphid Cluster Detection and Segmentation in Sorghum Fields","created":"2024-05-07","cited_by_count":3,"area":null}],"next_cursor":"100"}