PRISM: A Multi-View Multi-Capability Retail Video Dataset for Embodied Vision-Language Models

1. 1Collect and annotate a large-scale video dataset from multiple views in retail environments
2. 2Use the dataset for supervised fine-tuning of embodied vision-language models
3. 3Evaluate the performance of the fine-tuned models in real-world retail environments
4. 4Apply the learned models to various retail applications such as product recognition and customer behavior analysis

Computer vision engineers and AI researchers on a team can benefit from PRISM to improve the performance of vision-language models in real-world retail environments, as it provides a large-scale dataset for supervised fine-tuning

💡 PRISM addresses the gap between general-purpose visual understanding and specialized perceptual demands of real-world deployment environments

📹 Introducing PRISM, a 270K-sample video dataset for fine-tuning embodied vision-language models in retail #AI #ComputerVision