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cs.CV2025

VLM-AD: End-to-End Autonomous Driving through Vision-Language Model Supervision

Yi Xu, Yuxin Hu, Zaiwei Zhang +5

Human drivers rely on commonsense reasoning to navigate diverse and dynamic real-world scenarios. Existing end-to-end (E2E) autonomous driving (AD) models are typically optimized t…

cs.CV2024

Flash3D: Super-scaling Point Transformers through Joint Hardware-Geometry Locality

Liyan Chen, Gregory P. Meyer, Zaiwei Zhang +2

Recent efforts recognize the power of scale in 3D learning (e.g. PTv3) and attention mechanisms (e.g. FlashAttention). However, current point cloud backbones fail to holistically u…

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…

cs.CV2024

ViP-LLaVA: Making Large Multimodal Models Understand Arbitrary Visual Prompts

Mu Cai, Haotian Liu, Dennis Park +4

While existing large vision-language multimodal models focus on whole image understanding, there is a prominent gap in achieving region-specific comprehension. Current approaches t…