Summary of Integrating Object Detection Modality Into Visual Language Model For Enhanced Autonomous Driving Agent, by Linfeng He et al.
Integrating Object Detection Modality into Visual Language Model for Enhanced Autonomous Driving Agent
by Linfeng He, Yiming Sun, Sihao Wu, Jiaxu Liu, Xiaowei Huang
First submitted to arxiv on: 8 Nov 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A novel framework for enhancing visual comprehension in autonomous driving systems is proposed by integrating visual language models (VLMs) with an additional visual perception module specialized in object detection. The Llama-Adapter architecture is extended to incorporate a YOLOS-based detection network alongside the CLIP perception network, addressing limitations in object detection and localization. Camera ID-separators are introduced to improve multi-view processing, which is crucial for comprehensive environmental awareness. Experiments on the DriveLM visual question answering challenge demonstrate significant improvements over baseline models, with enhanced performance in ChatGPT scores, BLEU scores, and CIDEr metrics. This approach represents a promising step towards more capable and interpretable autonomous driving systems. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary In this paper, researchers created a new way to make self-driving cars better at understanding what they see. They combined two types of computer vision models to improve object detection and localization. The new model is good at processing information from different cameras and can be used to make self-driving cars safer. It performed well in tests and could lead to more reliable autonomous driving systems. |
Keywords
» Artificial intelligence » Bleu » Llama » Object detection » Question answering
