6 citations · 11 across the 4 of their papers we have counts for
4 papers
Incremental Few-Shot Learning via Implanting and Compressing
Yiting Li, Haiyue Zhu, Xijia Feng +5
This work focuses on tackling the challenging but realistic visual task of Incremental Few-Shot Learning (IFSL), which requires a model to continually learn novel classes from only…
Towards Generalized and Incremental Few-Shot Object Detection
Yiting Li, Haiyue Zhu, Jun Ma +4
Real-world object detection is highly desired to be equipped with the learning expandability that can enlarge its detection classes incrementally. Moreover, such learning from only…
Grasping Detection Network with Uncertainty Estimation for Confidence-Driven Semi-Supervised Domain Adaptation
Haiyue Zhu, Yiting Li, Fengjun Bai +6
Data-efficient domain adaptation with only a few labelled data is desired for many robotic applications, e.g., in grasping detection, the inference skill learned from a grasping da…
Incremental Few-Shot Object Detection for Robotics
Yiting Li, Haiyue Zhu, Sichao Tian +6
Incremental few-shot learning is highly expected for practical robotics applications. On one hand, robot is desired to learn new tasks quickly and flexibly using only few annotated…