DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection
Ziyuan Zhao (Nanyang Technological University),* Mingxi Xu (Nanyang Technological University), Peisheng Qian (I2R, A*STAR), Ramanpreet Pahwa (I2R), richard chang (Institute for Infocomm Research)
The 33rd British Machine Vision Conference
Abstract
Deep learning has achieved notable success in 3D object detection with the advent of large-scale point cloud datasets. However, severe performance degradation in the past trained classes, i.e., catastrophic forgetting, still remains a critical issue for real-world deployment when the number of classes is unknown or may vary. Moreover, existing 3D class-incremental detection methods are developed for the single-domain scenario, which fail when encountering domain shift caused by different datasets, varying environments, etc. In this paper, we identify the unexplored yet valuable scenario, i.e., class-incremental learning under domain shift, and propose a novel 3D domain adaptive class-incremental object detection framework, DA-CIL, in which we design a novel dual-domain copy-paste augmentation method to construct multiple augmented domains for diversifying training distributions, thereby facilitating gradual domain adaptation. Then, multi-level consistency is explored to facilitate dual-teacher knowledge distillation from different domains for domain adaptive class-incremental learning. Extensive experiments on various datasets demonstrate the effectiveness of the proposed method over baselines in the domain adaptive class-incremental learning scenario.Video
Citation
@inproceedings{Zhao_2022_BMVC,
author = {Ziyuan Zhao and Mingxi Xu and Peisheng Qian and Ramanpreet Pahwa and richard chang},
title = {DA-CIL: Towards Domain Adaptive Class-Incremental 3D Object Detection},
booktitle = {33rd British Machine Vision Conference 2022, {BMVC} 2022, London, UK, November 21-24, 2022},
publisher = {{BMVA} Press},
year = {2022},
url = {https://bmvc2022.mpi-inf.mpg.de/0916.pdf}
}
Copyright © 2022
The British Machine Vision Conference is organised by