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Hehn, T.M. (author), Kooij, J.F.P. (author), Gavrila, D. (author)
State-of-the-art stixel methods fuse dense stereo and semantic class information, e.g. from a Convolutional Neural Network (CNN), into a compact representation of driveable space, obstacles, and background. However, they do not explicitly differentiate instances within the same class. We investigate several ways to augment single-frame stixels...
conference paper 2019