3 papers
cs.CV2024
Uncertainty-Guided Enhancement on Driving Perception System via Foundation Models
Yunhao Yang, Yuxin Hu, Mao Ye +5
Multimodal foundation models offer promising advancements for enhancing driving perception systems, but their high computational and financial costs pose challenges. We develop a m…
cs.CV2024
VLMine: Long-Tail Data Mining with Vision Language Models
Mao Ye, Gregory P. Meyer, Zaiwei Zhang +4
Ensuring robust performance on long-tail examples is an important problem for many real-world applications of machine learning, such as autonomous driving. This work focuses on the…
cs.CV2024
VLM-KD: Knowledge Distillation from VLM for Long-Tail Visual Recognition
Zaiwei Zhang, Gregory P. Meyer, Zhichao Lu +3
For visual recognition, knowledge distillation typically involves transferring knowledge from a large, well-trained teacher model to a smaller student model. In this paper, we intr…