107 citations · 162 across the 15 of their papers we have counts for
3 papers · 1 filter
Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networks
Guangxing Han, Yicheng He, Shiyuan Huang +2
Few-shot object detection (FSOD) aims to detect never-seen objects using few examples. This field sees recent improvement owing to the meta-learning techniques by learning how to m…
Partner-Assisted Learning for Few-Shot Image Classification
Jiawei Ma, Hanchen Xie, Guangxing Han +3
Few-shot Learning has been studied to mimic human visual capabilities and learn effective models without the need of exhaustive human annotation. Even though the idea of meta-learn…
Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment
Guangxing Han, Shiyuan Huang, Jiawei Ma +2
Few-shot object detection (FSOD) aims to detect objects using only a few examples. How to adapt state-of-the-art object detectors to the few-shot domain remains challenging. Object…