Shijian Lu

Unsupervised Domain Adaptive 3D Detection with Multi-Level Consistency

2021 · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Deep learning-based 3D object detection has achieved unprecedented success with the advent of large-scale autonomous driving datasets. However, drastic performance degradation remains a critical challenge for cross-domain deployment. In addition, existing 3D domain adaptive detection …

Class-Independent Regularization for Learning with Noisy Labels

2023 · Proceedings of the AAAI Conference on Artificial Intelligence

Training deep neural networks (DNNs) with noisy labels often leads to poorly generalized models as DNNs tend to memorize the noisy labels in training. Various strategies have been developed for improving sample selection precision and …

Black-box Unsupervised Domain Adaptation with Bi-directional Atkinson-Shiffrin Memory

2023

Black-box unsupervised domain adaptation (UDA) learns with source predictions of target data without accessing either source data or source models during training, and it has clear superiority in data privacy and flexibility in target network …