17 citations · 19 across the 3 of their papers we have counts for
3 papers
cs.CV2021★ 1 cited
Binocular Mutual Learning for Improving Few-shot Classification
Ziqi Zhou, Xi Qiu, Jiangtao Xie +2
Most of the few-shot learning methods learn to transfer knowledge from datasets with abundant labeled data (i.e., the base set). From the perspective of class space on base set, ex…
cs.CV2021★ 17 cited
DeFRCN: Decoupled Faster R-CNN for Few-Shot Object Detection
Limeng Qiao, Yuxuan Zhao, Zhiyuan Li +3
Few-shot object detection, which aims at detecting novel objects rapidly from extremely few annotated examples of previously unseen classes, has attracted significant research inte…
cs.CV2020★ 1 cited
SQE: a Self Quality Evaluation Metric for Parameters Optimization in Multi-Object Tracking
Yanru Huang, Feiyu Zhu, Zheni Zeng +3
We present a novel self quality evaluation metric SQE for parameters optimization in the challenging yet critical multi-object tracking task. Current evaluation metrics all require…