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publication about this benchmark. # Cea List Moyens / Méthodes / Logiciels AI, Deep Neural Network, Computer Vision, Human behavior analysis Profil du candidat Profile - Students in their 4th or 5th year
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/Computer Vision pour analyser les images radioscopiques d'un mélange triphasique. Stage M2 de traitement et d'analyse d'images issues de radioscopies X de mélanges triphasiques. Mise en œuvre de méthodes de
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gaussian representation meets perception models for bev segmentation. In : 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). IEEE, 2025. p. 2250-2259. [3] KERBL, Bernhard, KOPANAS
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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
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workspace learning,” in European Conference on Computer Vision, 2026. [3] A. Brazi, B. Meden, F. M. de Chamisso, S. Bourgeois, and V. Lepetit, “Corr2distrib: Making ambiguous correspondences an ally to
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promising industrial sectors. In this context, artificial intelligence (AI) algorithms have undoubtedly demonstrated their effectiveness for tasks related to vision, with various sensors (camera
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of Textual and Visual Semantic Analysis (LASTI) conducts its research in the field of natural language processing and computer vision to extract, classify and generate information. The laboratory's
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computer vision). - Maîtrise de la programmation en Python et des frameworks comme PyTorch ou TensorFlow. - Expérience (un plus) avec des modèles de segmentation (YOLO, U-Net, etc.). Conformément aux
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for High-Performance Automotive ADAS & Autonomous Driving, Product Folder. [7] K. He, X. Zhang, S. Ren, and J. Sun, "Deep Residual Learning for Image Recognition," IEEE Conference on Computer Vision
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as neural radiance fields for view synthesis. In European Conference on Computer Vision (ECCV), 2020. [2] Kerbl, B., Kopanas, G., Leimkuhler, T., Drettakis, G. (2023). 3d gaussian splatting for real