From Virtual to Real World Visual Perception using Domain Adaptation - The DPM as Example
Domain Adaptation in Computer Vision Applications, 2017.
Supervised learning tends to produce more accurate classifiers than unsupervised learning in general. This implies that training data is preferred with annotations. When addressing visual perception challenges, such as localizing certain object classes within an image, the learning of the involved classifiers turns out to be a practical b...More
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