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Titlebook: Computer Vision – ECCV 2022 Workshops; Tel Aviv, Israel, Oc Leonid Karlinsky,Tomer Michaeli,Ko Nishino Conference proceedings 2023 The Edit

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Hearing, Noise, and Echolocating Odontoceteschronously to update a Kalman filter that estimates star position and velocity in an image. The proposed tracking method is validated on real and simulated data and shows state-of-that-art tracking performance against existing approach.
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https://doi.org/10.1007/978-981-99-6335-5, tailoring the style parameterization on a per-region basis using a semantic map of the facial regions. We show HyperNST to exceed state of the art in content preservation for our stylized content while retaining good style transfer performance.
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https://doi.org/10.1007/978-981-99-6335-5t classification problems and use them as a surrogate for studying the TL potential of four popular VTs. Their performance is extensively compared against that of four common CNNs across several TL experiments. Our results show that VTs exhibit strong generalization properties and that these networks are more powerful feature extractors than CNNs.
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Asynchronous Kalman Filter for Event-Based Star Trackingchronously to update a Kalman filter that estimates star position and velocity in an image. The proposed tracking method is validated on real and simulated data and shows state-of-that-art tracking performance against existing approach.
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