A25 - Computer Vision by Learning

From: April 1 to 5, 2019


This graduate course is especially meant for Ph.D. students who have basic familiarity with computer vision, image processing, and machine learning and want to upsurge their knowledge and machinery to the state-of-the-art, with direct utility in their own research.

The topic of attention is the challenge of computer vision by learning. We address the theoretical foundations of computer vision in conjunction with machine learning and present algorithms that achieve state-of-the-art performance while maintaining efficient execution with minimal supervision. This year we explain and emphasize on computer vision by deep learning, including challenges like image classification by data-efficient convolutional neural networks, face generation by Generative Adversarial Networks, action recognition with point-supervision, and explainability by vision and language embeddings. We give an overview of the latest developments and future trends in the field on the basis of several recent challenges, and we indicate how to obtain improvements in the near future.

For the course schedule please click here.


Science Park 123


Route to CWI-Eulerzaal

Route to Cafe Polder


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