{"total":36,"rows":[{"id":"2103.11402","title":"Instant-Teaching: An End-to-End Semi-Supervised Object Detection Framework","created":"2021-03-21","cited_by_count":113,"area":null},{"id":"2208.11296","title":"Semi-Supervised and Unsupervised Deep Visual Learning: A Survey","created":"2022-08-24","cited_by_count":52,"area":null},{"id":"2103.16368","title":"Data-Uncertainty Guided Multi-Phase Learning for Semi-Supervised Object Detection","created":"2021-03-29","cited_by_count":49,"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":"2107.05031","title":"Semi-Supervised Object Detection with Adaptive Class-Rebalancing Self-Training","created":"2021-07-11","cited_by_count":28,"area":null},{"id":"2106.11921","title":"Not All Labels Are Equal: Rationalizing The Labeling Costs for Training Object Detection","created":"2021-06-22","cited_by_count":27,"area":null},{"id":"2204.07262","title":"Imposing Consistency for Optical Flow Estimation","created":"2022-04-14","cited_by_count":24,"area":null},{"id":"2207.04448","title":"Mix-Teaching: A Simple, Unified and Effective Semi-Supervised Learning Framework for Monocular 3D Object Detection","created":"2022-07-10","cited_by_count":23,"area":null},{"id":"2111.00928","title":"Combating Noise: Semi-supervised Learning by Region Uncertainty Quantification","created":"2021-11-01","cited_by_count":18,"area":null},{"id":"2203.04251","title":"End-to-End Semi-Supervised Learning for Video Action Detection","created":"2022-03-08","cited_by_count":17,"area":null},{"id":"2303.14078","title":"DistractFlow: Improving Optical Flow Estimation via Realistic Distractions and Pseudo-Labeling","created":"2023-03-24","cited_by_count":14,"area":null},{"id":"2206.00274","title":"Point-Teaching: Weakly Semi-Supervised Object Detection with Point Annotations","created":"2022-06-01","cited_by_count":11,"area":null},{"id":"2403.18092","title":"OCAI: Improving Optical Flow Estimation by Occlusion and Consistency Aware Interpolation","created":"2024-03-26","cited_by_count":11,"area":null},{"id":"2203.15353","title":"SIOD: Single Instance Annotated Per Category Per Image for Object Detection","created":"2022-03-29","cited_by_count":10,"area":null},{"id":"2312.07006","title":"Mixed Pseudo Labels for Semi-Supervised Object Detection","created":"2023-12-12","cited_by_count":10,"area":null},{"id":"2105.11293","title":"WSSOD: A New Pipeline for Weakly- and Semi-Supervised Object Detection","created":"2021-05-21","cited_by_count":7,"area":null},{"id":"2407.03251","title":"ACTRESS: Active Retraining for Semi-supervised Visual Grounding","created":"2024-07-03","cited_by_count":7,"area":null},{"id":"2201.10734","title":"CrossRectify: Leveraging Disagreement for Semi-supervised Object Detection","created":"2022-01-26","cited_by_count":6,"area":null},{"id":"2204.04492","title":"S4OD: Semi-Supervised learning for Single-Stage Object Detection","created":"2022-04-09","cited_by_count":6,"area":null},{"id":"2212.13381","title":"MixupE: Understanding and Improving Mixup from Directional Derivative Perspective","created":"2022-12-27","cited_by_count":6,"area":null},{"id":"2212.02747","title":"Semi-Supervised Object Detection with Object-wise Contrastive Learning and Regression Uncertainty","created":"2022-12-06","cited_by_count":5,"area":null},{"id":"2306.14106","title":"Semi-supervised Object Detection: A Survey on Recent Research and Progress","created":"2023-06-25","cited_by_count":5,"area":null},{"id":"2204.00147","title":"Semi-Weakly Supervised Object Detection by Sampling Pseudo Ground-Truth Boxes","created":"2022-04-01","cited_by_count":3,"area":null},{"id":"2303.02998","title":"Pseudo-label Correction and Learning For Semi-Supervised Object Detection","created":"2023-03-06","cited_by_count":3,"area":null},{"id":"2303.10343","title":"Supervision Interpolation via LossMix: Generalizing Mixup for Object Detection and Beyond","created":"2023-03-18","cited_by_count":3,"area":null},{"id":"2112.08605","title":"Frequency Spectrum Augmentation Consistency for Domain Adaptive Object Detection","created":"2021-12-16","cited_by_count":2,"area":null},{"id":"2210.10221","title":"Non-iterative optimization of pseudo-labeling thresholds for training object detection models from multiple datasets","created":"2022-10-19","cited_by_count":2,"area":null},{"id":"2305.14813","title":"Semi-Supervised and Long-Tailed Object Detection with CascadeMatch","created":"2023-05-24","cited_by_count":2,"area":null},{"id":"2302.11299","title":"Towards End-to-end Semi-supervised Learning for One-stage Object Detection","created":"2023-02-22","cited_by_count":1,"area":null},{"id":"2306.15898","title":"Pseudo-Labeling Enhanced by Privileged Information and Its Application to In Situ Sequencing Images","created":"2023-06-28","cited_by_count":1,"area":null},{"id":"2311.06054","title":"Refining the ONCE Benchmark with Hyperparameter Tuning","created":"2023-11-10","cited_by_count":1,"area":null},{"id":"2510.19330","title":"Exploring Scale Shift in Crowd Localization under the Context of Domain Generalization","created":"2025-10-22","cited_by_count":1,"area":null},{"id":"2207.09609","title":"Towards Accurate and Robust Classification in Continuously Transitioning Industrial Sprays with Mixup","created":"2022-07-20","cited_by_count":0,"area":null},{"id":"2310.08387","title":"Aligning Data Selection with Performance: Performance-driven Reinforcement Learning for Active Learning in Object Detection","created":"2023-10-12","cited_by_count":0,"area":null},{"id":"2310.14718","title":"Rethinking Scale Imbalance in Semi-supervised Object Detection for Aerial Images","created":"2023-10-23","cited_by_count":0,"area":null},{"id":"2407.11073","title":"SemiAdv: Query-Efficient Black-Box Adversarial Attack with Unlabeled Images","created":"2024-07-13","cited_by_count":0,"area":null}],"next_cursor":null}