Internship 3D Reconstruction in the Dark: Radiance Fields for Unlit Environments-Saclay-H/F
Il y a 1 jour
Saclay, Ile-de-France
CEA
Temps plein
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As an intern at the CEA, you will have the opportunity to work within a world-renowned research environment. Our teams consist of passionate and dedicated experts, providing an ideal setting for learning and collaboration. You will have access to state-of-the-art equipment and top-tier research resources to carry out your assignments. The work conducted may potentially lead to a scientific publication.
What do we expect from you?
The intern will be responsible for:
• State of the Art Review: Analyzing existing 3D reconstruction methods (NeRF, Gaussian Splatting) and their limitations in unlit environments.
• Prototyping: Implementing a solution that model the light source in the inverse rendering reconstruction pipeline.
• Experimentation: Testing the system in real or simulated scenarios, with different light configurations.
• Optimization: Improving robustness and the reconstruction accuracy (large environment, reflective sufaces)
• Validation: Comparing results with classical methods (with fixed lighting) and evaluating improvements in quality and robustness. # Cea-List Moyens / Méthodes / Logiciels python Profil du candidat
• Currently enrolled in your final year of a Master's program (M2) or an Engineering School (including gap year students).
• Strong skills in computer vision and machine learning, particularly.
• High proficiency in Python alongside experience using a deep learning framework, with a strong preference for PyTorch. Localisation du poste Site Saclay Localisation du poste France, Ile-de-France, Essonne (91) Ville Saclay Critères candidat Diplôme préparé Bac+5
- Master 2
• State of the Art Review: Analyzing existing 3D reconstruction methods (NeRF, Gaussian Splatting) and their limitations in unlit environments.
• Prototyping: Implementing a solution that model the light source in the inverse rendering reconstruction pipeline.
• Experimentation: Testing the system in real or simulated scenarios, with different light configurations.
• Optimization: Improving robustness and the reconstruction accuracy (large environment, reflective sufaces)
• Validation: Comparing results with classical methods (with fixed lighting) and evaluating improvements in quality and robustness. # Cea-List Moyens / Méthodes / Logiciels python Profil du candidat
• Currently enrolled in your final year of a Master's program (M2) or an Engineering School (including gap year students).
• Strong skills in computer vision and machine learning, particularly.
• High proficiency in Python alongside experience using a deep learning framework, with a strong preference for PyTorch. Localisation du poste Site Saclay Localisation du poste France, Ile-de-France, Essonne (91) Ville Saclay Critères candidat Diplôme préparé Bac+5
- Master 2