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https://arxiv.org/abs/1708.02002 Focal Loss for Dense Object Detection The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is applied to a sparse set of candidate object locations. In contrast, one-stage detectors that are applied over a regular, dense sampl arxiv.org abstract 높은 정확도의 object detector는 two stage 방법으로 부족한 객체에 대한 ..

https://arxiv.org/abs/1905.01436 Edge-labeling Graph Neural Network for Few-shot Learning In this paper, we propose a novel edge-labeling graph neural network (EGNN), which adapts a deep neural network on the edge-labeling graph, for few-shot learning. The previous graph neural network (GNN) approaches in few-shot learning have been based on th arxiv.org abstract