Open-Set Object Detection: challenging VLM to understand unknown objects & contexts H/F

Job description: Your missions within this internship are to: • Study state-of-the-art methods of Open Set Object Detection (OSOD) as well as Visual Language Models (VLM) in the context of Open World containing both known and unknown objects; • Design an object detector aware of the existence of the unknown, and able to describe the unknown by comparing it to or distinguishing it from what is known via certain characteristics that can be described textually; • Evaluate the proposed method on recent OSOD benchmarks and compare to the state of the art; • Challenge these methods by applying them to new contexts (e.g. aerial images, medical imaging); • If relevant, submit your contributions to an international conference or workshop for publication. Join CEA List and LVA as an intern to: • Work in one of the most innovative research organizations in the world, addressing societal challenges to build the world of tomorrow • Discover a rich ecosystem: privileged connections between the industrial and academic sectors • Conduct research autonomously and creatively: encouragement to valorize 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 • Have the possibility of remote work, receive a 75% reimbursement on public transportation costs, and benefit from the “mobili-jeune” aid to reduce rent costs…

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 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.

Your profile: Students in their 5th year of studies (M2) • Computer vision skills • Machine learning skills (deep learning, VLM…) • Python proficiency in a deep learning framework (especially PyTorch)

Level of qualification studied: Bac+5 - Master of Science