PFM-VEPAR: Prompting Foundation Models for RGB-Event Camera based Pedestrian Attribute Recognition
📰 ArXiv cs.AI
Researchers propose PFM-VEPAR, a method for prompting foundation models to recognize pedestrian attributes using RGB-Event cameras
Action Steps
- Propose an Event Prompter to leverage motion cues from event cameras
- Discard traditional two-stream multimodal fusion methods to reduce computational overhead
- Utilize contextual samples to guide the prompting of foundation models
- Evaluate the performance of PFM-VEPAR on pedestrian attribute recognition tasks
Who Needs to Know This
Computer vision engineers and researchers on a team can benefit from this method to improve pedestrian attribute recognition in low-light and motion-blur scenarios, and it can be applied by AI engineers and ML researchers to develop more accurate models
Key Insight
💡 PFM-VEPAR can improve pedestrian attribute recognition in low-light and motion-blur scenarios by leveraging motion cues from event cameras
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🚶♀️💻 PFM-VEPAR: Prompting foundation models for RGB-Event camera based pedestrian attribute recognition
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