4 papers
Is Pre-training Truly Better Than Meta-Learning?
Brando Miranda, Patrick Yu, Saumya Goyal +2
In the context of few-shot learning, it is currently believed that a fixed pre-trained (PT) model, along with fine-tuning the final layer during evaluation, outperforms standard me…
Generalized Open-World Semi-Supervised Object Detection
Garvita Allabadi, Ana Lucic, Siddarth Aananth +3
Traditional semi-supervised object detection methods assume a fixed set of object classes (in-distribution or ID classes) during training and deployment, which limits performance i…
Do Pre-trained Models Benefit Equally in Continual Learning?
Kuan-Ying Lee, Yuanyi Zhong, Yu-Xiong Wang
Existing work on continual learning (CL) is primarily devoted to developing algorithms for models trained from scratch. Despite their encouraging performance on contrived benchmark…
DualCross: Cross-Modality Cross-Domain Adaptation for Monocular BEV Perception
Yunze Man, Liang-Yan Gui, Yu-Xiong Wang
Closing the domain gap between training and deployment and incorporating multiple sensor modalities are two challenging yet critical topics for self-driving. Existing work only foc…