Open-Set Object Detection: Can VLM understand all of the unknown world? H/F
Commissariat à l’Énergie Atomique
Organisation The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
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 FranceReference 2024-33175Description de l’unitéBased 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 industrialpartners, 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 visionand 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.Position descriptionCategoryMathematics, information, scientific, softwareContractInternshipJob titleOpen-Set Object Detection: Can VLM understand all of the unknown world? H/FSubjectDeep learning models have demonstrated significant success to detect a close set of known annotated classes seen during training. But, how will they behave when facing up to objects of unknown classes?
As their behaviour is uncertain when subjected to never-before-seen classes, we aim to develop robust Open Set ObjectDetectors (OSOD), able to localise and classify any objects, no matter their classes are known or unknown during training.
It is of paramount importance to ensure safe deployment of AI models as trustable AI is crucial in critical applications such as autonomous driving. Indeed, one of the most important issues for these applications is the lack of supervisory signals on data notseen in training, which can generate erroneous yet confident predictions on out-of-distribution (OOD) data.Contract duration (months)6Job descriptionYour missions within this internship are to:
Methods / MeansComputer vision, deep learning, VLM, pytorchApplicant ProfileJoin CEA List and LVA as an intern to:
In line with CEA’s commitment to integrating people with disabilities, this job is open to all.Position locationSiteSaclayJob locationFrance, Ile-de-France, Essonne (91)LocationPalaiseauCandidate criteriaPrepared diplomaBac+5 – Master of ScienceRecommended trainingMaster / école d’ingénieur en computer vision / AIPhD opportunityOuiRequesterPosition start date01/02/2025
€1300 – 1400 per month
Essonne
Sat, 28 Sep 2024 00:18:48 GMT
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