Image Editing of Complex Visual Scene via Natural Language H/F
il y a 7 jours
General information
Organisation
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.
Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.
The CEA is established in ten centers spread throughout France
Reference
Description de l'unité
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 and Learning for Scene Analysis (LVA) 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 visual recognition, behavior and activity analysis, large-scale automatic annotation, and perception and decision models.
Category
Information system
Contract
Internship
Job title
Image Editing of Complex Visual Scene via Natural Language H/F
Subject
This internship focuses on natural language-guided image editing, aiming at generating and modifying complex scenes from verbal descriptions. The candidate will design and implement methods to interpret language for creating or editing detailed images (e.g., crowds, cityscapes, multi-object interactions). Key challenges include managing scene complexity—ensuring coherence and accuracy when multiple objects and relations are involved—and achieving effective multimodal integration between NLP and vision models.
Contract duration (months)
6
Job description
This internship focuses on the emerging field of natural language-guided image editing, specifically targeting the generation and modification of complex scenes based on verbal descriptions. The candidate will work on designing and implementing novel methods that can interpret natural language to manipulate or generate detailed images representing multifaceted scenarios (e.g., crowd scenes, cityscapes, interactions between multiple objects).
This project presents several key challenges, including:
•Scene Complexity: Managing multiple objects and their relationships in a scene adds significant complexity. The goal is to maintain coherence and accuracy in the edited images, even when the scenes described involve intricate interactions between various elements.
•Multimodal Integration: Successfully combining linguistic and visual inputs to obtain visual outputs, is a complex problem requiring seamless interaction between natural language processing (NLP) and computer vision models.
The objectives of this internship are to:
•Investigate current methods for natural language-based image generation and editing of complex scenes (in particular for the numerality and geometric positioning aspects);
•Develop an innovative approach for editing complex scenes using natural language descriptions;
•Demonstrate significant improvements in the accuracy and detail of generated images;
•Contribute to academic research through potential publications and/or patents.
Methods / Means
Computer Vision / ML (deep learning, GenAI…); Python (PyTorch, TensorFlow)
Applicant Profile
•Students in their 5th year of studies (M2)
•Computer vision skills
•Machine learning skills (deep learning, LLM, VLM, generative AI…)
•Python proficiency in a deep learning framework (especially PyTorch or TensorFlow)
Site
Saclay
Job location
France, Ile-de-France, Essonne (91)
Location
Saclay
Languages
English (Fluent)
Prepared diploma
Bac+5 - Diplôme École d'ingénieurs
Recommended training
Students in their 5th year of studies (M2)
PhD opportunity
Oui
Position start date
02/02/2026
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