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  • [2003. 06957] Frustratingly Simple Few-Shot Object Detection
    We 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
  • 少样本目标检测 | TFA | Frustratingly Simple Few-Shot . . .
    基于COCO，生成多组（9组）不同seed的few-shot dataset，详见 prepare_coco_few_shot py，代码逻辑如下： 对于某个seed、某个class的多个k-shot：3-shot dataset包括1-shot dataset、5-shot dataset包括3-shot dataset，以此类推……
  • Frustratingly simple few-shot object detection
    As a challenging problem in machine learning, incremental few-shot object detection (iFSD) [1] aims to incrementally detect novel classes with few examples, while keeping the previous knowledge without revisiting base classes
  • Frustratingly Simple Few-Shot Object Detection - PMLR
    We 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
  • 【小样本目标检测】Frustratingly Simple Few-Shot Object . . .
    基于元学习的方法检测得到的效果会比微调的好，微调的方法通常被用作baseline。 太注重novel类的检测效果，而忽略了base类准确率下降的影响。 由于novel的样本较少，样本间的方差较大。 这样评估的性能受到方差的影响会有较大的波动，这个波动可能会较大地影响结果，从而得到不准确地评估性能。 作者发现，仅对novel类检测器的最后一层（分类器和回归器）进行微调，得到的效果非常显著。 在目前的基准测试中，这种简单的方法比元学习方法提高了大约2~20个点，有时甚至是以前方法的两倍精度。 在提高novel类检测精度的同时，还能保持base类的检测精度不下降。 提出了bAP和nAP来代表性能，并且增加随机抽样和重复评估过程获得一个较准确地评估benchmark。
  • ucbdrive few-shot-object-detection - GitHub
    FsDet contains the official few-shot object detection implementation of the ICML 2020 paper Frustratingly Simple Few-Shot Object Detection In addition to the benchmarks used by previous works, we introduce new benchmarks on three datasets: PASCAL VOC, COCO, and LVIS
  • 小样本目标检测：few-shot-object-detection训练自己的数据 . . .
    Frustratingly Simple Few-Shot Object Detection 除了以前工作中使用的基础，我们还在三个 数据集 上引入了新的基准：PASCAL VOC，COCO和LVIS。 我们对多组实验的多次抽样训练样本进行了抽样，并报告了基础班和新颖班的评估结果。 这些在 Data Preparation 中有更详细的
  • 【代码调试】《Frustratingly Simple Few-Shot Object . . .
    `np str` was a deprecated alias for the builtin `str` To avoid this error in existing code, use ` str` by itself
  • 【文章阅读】Frustratingly Simple Few-Shot Object Detection
    We proposed a simple two-stage fine-tuning approach for few-shot object detection Our method outperformed the previous meta-learning methods by a large margin on the current benchmarks





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