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Segmentation and Object Detection in Neural Radiance Fields (NeRFs) for Enhanced 3D Scene Understanding
This master thesis project focuses on advancing 3D scene understanding through the integration of segmentation and object detection techniques within Neural Radiance Fields (NeRFs).
This master thesis project focuses on advancing 3D scene understanding through the integration of segmentation and object detection techniques within Neural Radiance Fields (NeRFs). NeRFs have demonstrated remarkable capabilities in synthesizing high-fidelity 3D scenes, and this project aims to enhance their functionality by incorporating state-of-the-art methods for accurate segmentation and object detection. The student will explore novel approaches to seamlessly integrate these techniques, enabling NeRFs to not only generate realistic scenes but also identify and categorize objects within them. The project's scope includes experimentation with diverse datasets and validation through quantitative metrics to evaluate the effectiveness of the proposed methodology.
This master thesis project focuses on advancing 3D scene understanding through the integration of segmentation and object detection techniques within Neural Radiance Fields (NeRFs). NeRFs have demonstrated remarkable capabilities in synthesizing high-fidelity 3D scenes, and this project aims to enhance their functionality by incorporating state-of-the-art methods for accurate segmentation and object detection. The student will explore novel approaches to seamlessly integrate these techniques, enabling NeRFs to not only generate realistic scenes but also identify and categorize objects within them. The project's scope includes experimentation with diverse datasets and validation through quantitative metrics to evaluate the effectiveness of the proposed methodology.
The primary goal of this master thesis project is to enhance 3D scene understanding within Neural Radiance Fields (NeRFs) by integrating advanced segmentation and object detection techniques. Validation of the proposed approach will be conducted using diverse datasets, with a focus on quantitative metrics to demonstrate the effectiveness of the enhanced NeRF model.
The primary goal of this master thesis project is to enhance 3D scene understanding within Neural Radiance Fields (NeRFs) by integrating advanced segmentation and object detection techniques. Validation of the proposed approach will be conducted using diverse datasets, with a focus on quantitative metrics to demonstrate the effectiveness of the enhanced NeRF model.
Harmish Khambhaita (harmish@ifi.uzh.ch), Marco Cannici (cannici@ifi.uzh.ch)
Harmish Khambhaita (harmish@ifi.uzh.ch), Marco Cannici (cannici@ifi.uzh.ch)