Web27 okt. 2024 · Few-shot object detection (FSOD) aims to achieve excellent novel category object detection accuracy with few samples. ... Wang, Y.-X., Ramanan, D., Hebert, M.: Meta-learning to detect rare objects. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9925–9934 (2024) Web[ICCV 2024] Meta-Learning to Detect Rare Objects [ICCV 2024] SILCO: Show a Few Images, Localize the Common Object code [IEEE Access] Meta-SSD: Towards Fast Adaptation for Few-Shot Object Detection with Meta-Learning; 2024 [AAAI 2024] …

Meta-Learning to Detect Rare Objects - IEEE Xplore

Web4 nov. 2024 · 3. Meta-Learning based Object Detection. 下图展示了我们基于元学习的小样本目标检测方法“元集”的框架。. 通过学习大量的小样本检测任务，这些任务是在基类中模拟的，基类中有大量的带标注的数据，MetaDet允许我们快速生成一个检测器的新类只使用几个 … Web31 dec. 2024 · Meta-Learning based Object Detection 下图展示了我们基于元学习的小样本目标检测方法“元集”的框架。 通过学习大量的小样本检测任务，这些任务是在基类中模拟的，基类中有大量的带标注的数据，MetaDet允许我们快速生成一个检测器的新类只使用 … libreoffice hex2dec

[ICCV论文阅读2024]Meta-Learning to Detect Rare Objects

Webthis emerging field of few-shot object detection. Index Terms—Object Detection, Few-Shot Learning, Survey, Meta Learning, Transfer Learning I. INTRODUCTION In the last decade, object detection has tremendously im-proved through deep learning [1], [2]. However, deep-learning-based approaches typically require vast amounts of training data. Web1 okt. 2024 · After that, two phases of meta-learning to detect rare objects (MetaDet) [4] and towards general solver for instance-level low-shot learning [5] have been proposed. WebWe find that fine-tuning only the last layer of existing detectors on rare classes is crucial to the few-shot object detection task. Such a simple approach outperforms the meta-learning methods by roughly 2∼20 points on current benchmarks and sometimes even doubles the accuracy of the prior methods. libreoffice headless convert