Researchers from Tsinghua Shenzhen International Graduate School, Shanghai AI Laboratory, and Nanyang Technological University have developed RTMO, a one-stage pose estimation framework that combines coordinate classification and dense prediction models to enhance accuracy and efficiency. RTMO achieves higher Average Precision on COCO and real-time performance, outperforming existing methods. More details in the paper https://arxiv.org/abs/2312.07526v1.
RTMO: A Breakthrough in Real-Time Multi-Person Pose Estimation
Introduction
The field of pose estimation is rapidly evolving, and researchers from Tsinghua Shenzhen International Graduate School, Shanghai AI Laboratory, and Nanyang Technological University have developed a new RTMO framework that has the potential to enhance accuracy and efficiency in various applications, such as robotics, augmented reality, and virtual reality.
Key Features of RTMO
– RTMO is a one-stage pose estimation framework designed to overcome the trade-off between accuracy and real-time performance in existing methods.
– It integrates coordinate classification and dense prediction models, outperforming other one-stage pose estimators in terms of accuracy and speed.
– The framework employs a YOLO-like architecture with CSPDarknet as the backbone and a Hybrid Encoder, addressing incompatibilities between coordinate classification and dense prediction models.
– RTMO excels in multi-person pose estimation, achieving high accuracy and real-time performance, outperforming cutting-edge one-stage pose estimators in performance and speed.
Practical Applications
– RTMO can be applied in challenging multi-person scenarios, generating spatially accurate heatmaps for robust, context-aware predictions.
– The framework balances performance and speed, aligning with the needs of middle managers seeking practical AI solutions.
Next Steps
If you want to evolve your company with AI and stay competitive, consider utilizing RTMO for real-time multi-person pose estimation. It can redefine your way of work and automate customer engagement, ultimately enhancing your sales processes and customer interactions.
For more information, check out the research paper and connect with us for KPI management and practical AI solutions at hello@itinai.com. Stay updated on leveraging AI through our Telegram channel t.me/itinainews or Twitter @itinaicom.
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List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- This AI Paper Introduces RTMO: A Breakthrough in Real-Time Multi-Person Pose Estimation Using Dual 1-D Heatmaps
- MarkTechPost
- Twitter – @itinaicom
