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Computer Vision Researcher Interview Questions
35 computer vision researcher interview questions shared by candidates
3. Take home test - implement a method of Facial landmark localization from a paper called 'Supervised Descent Method and its Applications to Face Alignment' from 2013. Note - the instruction they provide implies it's more of a coding task, but they actually expect you to have a deep understanding of everything: * How the SIFT/HoG descriptors are computed and why? * Why augmentations are needed? * What's better to have and why (in terms of prediction accuracy) - one model to predict all landmark points or a different model for each point.
program a static NN in TensorFlow for AND Gate
How do you recover structure from a scene precisely without knowing anything.
2. On the zoom interview - Design a colorization model (given a grayscale image, predict its color).
The coding questions are quite simple. Research questions are about multi-view geometry, such as fundamental/essential matrix and deep learning basics (resnet, loss function, kernel size, pooling, dropout, batch norm, etc.). Generally the questions are not so difficult.
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1- Generate a list of Random Objects that each rand object generates a different sequence coming from the same set of values.
Questions about classification and object detection
epipolar geometry and machine learning optimization based on resume
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