Estimating the Robustness of Classification Models by the Structure of the Learned Feature-Space

no code implementations • AAAI Workshop AdvML 2022 • Kalun Ho, Franz-Josef Pfreundt, Janis Keuper, Margret Keuper

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 standardized benchmarks like ImageNet.

Clustering Image Classification

Latent Space Conditioning on Generative Adversarial Networks

no code implementations • 16 Dec 2020 • Ricard Durall, Kalun Ho, Franz-Josef Pfreundt, Janis Keuper

In particular, our approach exploits the structure of a latent space (learned by the representation learning) and employs it to condition the generative model.

Image Generation Representation Learning

Self-supervised Sparse to Dense Motion Segmentation

no code implementations • 18 Aug 2020 • Amirhossein Kardoost, Kalun Ho, Peter Ochs, Margret Keuper

We evaluate our method on the well-known motion segmentation datasets FBMS59 and DAVIS16.

Motion Segmentation Segmentation

Learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches

no code implementations • 6 Jul 2020 • Kalun Ho, Janis Keuper, Franz-Josef Pfreundt, Margret Keuper

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.

Clustering Image Classification +1

Unsupervised Multiple Person Tracking using AutoEncoder-Based Lifted Multicuts

no code implementations • 4 Feb 2020 • Kalun Ho, Janis Keuper, Margret Keuper

Our method is based on straight-forward spatio-temporal cues that can be extracted from neighboring frames in an image sequences without superivison.

Clustering Multiple Object Tracking