3 papers
cs.CV2024
Foundation Models for Amodal Video Instance Segmentation in Automated Driving
Jasmin Breitenstein, Franz Jünger, Andreas Bär +1
In this work, we study amodal video instance segmentation for automated driving. Previous works perform amodal video instance segmentation relying on methods trained on entirely la…
eess.AS2024
Non-Causal to Causal SSL-Supported Transfer Learning: Towards a High-Performance Low-Latency Speech Vocoder
Renzheng Shi, Andreas Bär, Marvin Sach +2
Recently, BigVGAN has emerged as high-performance speech vocoder. Its sequence-to-sequence-based synthesis, however, prohibits usage in low-latency conversational applications. Our…
cs.CV2024
Frozen Feature Augmentation for Few-Shot Image Classification
Andreas Bär, Neil Houlsby, Mostafa Dehghani +1
Training a linear classifier or lightweight model on top of pretrained vision model outputs, so-called 'frozen features', leads to impressive performance on a number of downstream…