8 citations · 10 across the 3 of their papers we have counts for
5 papers
Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space
Kalun Ho, Franz-Josef Pfreundt, Janis Keuper +1
Over the last decade, the development of deep image classification networks has mostly been driven by the search for the best performance in terms of classification accuracy on sta…
Latent Space Conditioning on Generative Adversarial Networks
Ricard Durall, Kalun Ho, Franz-Josef Pfreundt +1
Generative adversarial networks are the state of the art approach towards learned synthetic image generation. Although early successes were mostly unsupervised, bit by bit, this tr…
Self-supervised Sparse to Dense Motion Segmentation
Amirhossein Kardoost, Kalun Ho, Peter Ochs +1
Observable motion in videos can give rise to the definition of objects moving with respect to the scene. The task of segmenting such moving objects is referred to as motion segment…
Learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches
Kalun Ho, Janis Keuper, Franz-Josef Pfreundt +1
In this work, we evaluate two different image clustering objectives, k-means clustering and correlation clustering, in the context of Triplet Loss induced feature space embeddings.…
Unsupervised Multiple Person Tracking using AutoEncoder-Based Lifted Multicuts
Kalun Ho, Janis Keuper, Margret Keuper
Multiple Object Tracking (MOT) is a long-standing task in computer vision. Current approaches based on the tracking by detection paradigm either require some sort of domain knowled…