113 citations · 335 across the 25 of their papers we have counts for
4 papers · 1 filter
Decoupling Classifier for Boosting Few-shot Object Detection and Instance Segmentation
Bin-Bin Gao, Xiaochen Chen, Zhongyi Huang +6
This paper focus on few-shot object detection~(FSOD) and instance segmentation~(FSIS), which requires a model to quickly adapt to novel classes with a few labeled instances. The ex…
Clustered-patch Element Connection for Few-shot Learning
Jinxiang Lai, Siqian Yang, Junhong Zhou +5
Weak feature representation problem has influenced the performance of few-shot classification task for a long time. To alleviate this problem, recent researchers build connections…
Rethinking the Metric in Few-shot Learning: From an Adaptive Multi-Distance Perspective
Jinxiang Lai, Siqian Yang, Guannan Jiang +9
Few-shot learning problem focuses on recognizing unseen classes given a few labeled images. In recent effort, more attention is paid to fine-grained feature embedding, ignoring the…
A propagation matting method based on the Local Sampling and KNN Classification with adaptive feature space
Xiao Chen, Fazhi He
Closed Form is a propagation based matting algorithm, functioning well on images with good propagation . The deficiency of the Closed Form method is that for complex areas with poo…