Foundational models are critical in ML, particularly in tasks like Monocular Depth Estimation. Researchers from The University of Hong Kong, TikTok, Zhejiang Lab, and Zhejiang University developed a foundational model, “Depth Anything,” improving depth estimation using unlabeled data and leveraging pre-trained encoders. The model outperforms MiDaS in zero-shot depth estimation, showing potential for various visual perception tasks.
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Practical AI Solution for Robust Monocular Depth Estimation
Introduction
Foundational models are large deep-learning neural networks used as a starting point to develop effective ML models. They are invaluable in natural language processing, computer vision, Monocular Depth Estimation (MDE), and applications like autonomous vehicles, robotics, and virtual reality.
Research Innovation
The researchers have developed a foundational model for MDE that can produce high-quality depth information from images. They focused on using large-scale unlabeled data that are simple and cheap to acquire, diverse, and easy to annotate. Their work utilizes labeled and unlabeled data for better depth estimation, with the main focus on the latter.
Key Features
- Utilization of large-scale unlabeled data for better depth estimation
- Creation of a self-learning pipeline using labeled and unlabeled data
- Challenging the model with a tougher optimization target for additional knowledge
- Leveraging rich semantic priors from pre-trained encoders for better scene understanding
Evaluation and Results
The model outperforms the latest MiDaS model significantly across extensive scenes and on several unseen datasets. It also leads to better metric depth estimation than other models and shows superior results on MDE and semantic segmentation tasks.
Conclusion
Depth Anything is an effective solution for robust MDE as it primarily focuses on cheap and diverse unlabeled images. The model’s optimization target when learning unlabeled images is more challenging, leading to better performance and zero-shot estimation capabilities. It has the potential to be used in downstream depth estimation tasks.
For more information, check out the Paper and Github.
AI Solutions for Your Company
If you want to evolve your company with AI, consider using practical solutions like ‘Depth Anything’ for robust Monocular Depth Estimation. Identify automation opportunities, define KPIs, select an AI solution, and implement gradually to stay competitive in the AI landscape.
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