4 accepted papers
In computer vision and audio processing, soft dynamic time warping (SDTW) techniques have been used as a differentiable loss function to train deep neural networks (DNNs) on weakly aligned data. In existing SDTW algorithms, the horizontal, vertical, and diagonal alignment steps all have the same wei…
Many tasks in music information retrieval (MIR) involve weakly aligned data, where exact temporal correspondences are unknown. The connectionist temporal classification (CTC) loss is a standard technique to learn feature representations based on weakly aligned training data. However, CTC is limited…
Traditionally, work on singing voice detection has focused on identifying singing activity in music recordings. In this work, our aim is to extend this task towards simultaneously detecting the presence of singing voice as well as determining singer gender and voice type. We describe and compare fou…
This paper extends the popular task of multi-object tracking to multi-object tracking and segmentation (MOTS). Towards this goal, we create dense pixel-level annotations for two existing tracking datasets using a semi-automatic annotation procedure. Our new annotations comprise 65,213 pixel masks fo…