Accurate 3D scene reconstruction from images with neural Method H/F

Job description: Missions: During this internship, you will explore the state of the art techniques for 3D scene reconstruction from 2D image using Neural Fields. With a focus on the accuracy of reconstructed geometry, you will design and develop a method of 3D surface reconstruction, which will be applied to industrial environment. The internship will notably include: Reviewing existing literature on the topic Selecting and implementing an existing approaches in the Neural Fields framework NeRFStudio Benchmarking the new method using images capturing an industrial environment Job-related benefits Joining the CEA List and the LVML as an intern means: Working in one of the most innovative research organizations in the world, addressing societal challenges to build the world of tomorrow Discovering a rich ecosystem: privileged connections between the industrial and academic sectors Conducting research autonomously and creatively: encouragement to publish results (scientific articles, patents, open-source codes...) Join a young and dynamic team Benefit from an internal computing infrastructure with more than 300 state-of-the-art GPUs Receive a stipend between €1300 and €1400 per month Have the opportunity to continue with a PhD or as a research engineer after the internship Receive a 75% reimbursement on public transportation costs, and benefit from the “mobili-jeune” aid to reduce rent costs… #CEA-List

Institute description: Based in Saclay (Essonne), the LIST is one of the two institutes of CEA Tech, the Technological Research Division of the CEA. Dedicated to intelligent digital systems, its mission is to carry out technological developments of excellence on behalf of industrial partners, in order to create value. Within the LIST, the Laboratory of Vision for Modeling and Localization (LVML) conducts its research in the field of computer vision and artificial intelligence for the perception of intelligent and autonomous systems. The laboratory's research themes include 3D localization, segmentation, characterization and vision for robotics.

Your profile: Qualifications: Students in their 5th year of studies ( Master 2) or gap year Computer vision skills (3D vision, image processing) Python proficiency in a deep learning framework (preferably PyTorch

Level of qualification studied: Bac+5 - Master 2