Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints from Limited Training Data
arXiv: Computer Vision and Pattern Recognition, Volume abs/1811.11823, 2018.
Detecting semantic parts of an object is a challenging task in computer vision, particularly because it is hard to construct large annotated datasets due to the difficulty of annotating semantic parts. In this paper we present an approach which learns from a small training dataset of annotated semantic parts, where the object is seen from...More
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