Visual Learning With Weak Supervision
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Visual Learning with Weak Supervision
Most work in person re-identification has focused on a fixed network of cameras. However, in practice, new camera(s) may be added, either permanently or on a temporary basis. In the final part of the dissertation, we show that it is possible to on-board new camera(s) to an existing network using domain adaptation techniques with limited additional supervision. We develop a domain perceptive re-identification framework that can effectively discover and transfer knowledge from the best source camera (already installed) to a newly introduced target camera(s), without requiring a very expensive training phase. Our approach can greatly increase the flexibility and reduce the deployment cost of new cameras in many real-world dynamic camera networks.
Computer Vision – ECCV 2024
The multi-volume set of LNCS books with volume numbers 15059 up to 15147 constitutes the refereed proceedings of the 18th European Conference on Computer Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024. The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation.
Computer Vision – ECCV 2022
The 39-volume set, comprising the LNCS books 13661 until 13699, constitutes the refereed proceedings of the 17th European Conference on Computer Vision, ECCV 2022, held in Tel Aviv, Israel, during October 23–27, 2022. The 1645 papers presented in these proceedings were carefully reviewed and selected from a total of 5804 submissions. The papers deal with topics such as computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; image classification; image processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation.