5 citations · 10 across the 5 of their papers we have counts for
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cs.CV2023★ 3 cited
Explore the Power of Synthetic Data on Few-shot Object Detection
Shaobo Lin, Kun Wang, Xingyu Zeng +1
Few-shot object detection (FSOD) aims to expand an object detector for novel categories given only a few instances for training. The few training samples restrict the performance o…
cs.CV2023★ 2 cited
An Effective Crop-Paste Pipeline for Few-shot Object Detection
Shaobo Lin, Kun Wang, Xingyu Zeng +1
Few-shot object detection (FSOD) aims to expand an object detector for novel categories given only a few instances for training. However, detecting novel categories with only a few…
cs.CV2023
Explore the Power of Dropout on Few-shot Learning
Shaobo Lin, Xingyu Zeng, Rui Zhao
The generalization power of the pre-trained model is the key for few-shot deep learning. Dropout is a regularization technique used in traditional deep learning methods. In this pa…