5 citations · 8 across the 3 of their papers we have counts for
3 papers
ObjectVisA-120: Object-based Visual Attention Prediction in Interactive Street-crossing Environments
Igor Vozniak, Philipp Mueller, Nils Lipp +6
The object-based nature of human visual attention is well-known in cognitive science, but has only played a minor role in computational visual attention models so far. This is main…
Fine-Grained Semantic Segmentation of Motion Capture Data using Dilated Temporal Fully-Convolutional Networks
Noshaba Cheema, Somayeh Hosseini, Janis Sprenger +4
Human motion capture data has been widely used in data-driven character animation. In order to generate realistic, natural-looking motions, most data-driven approaches require cons…
Dilated Temporal Fully-Convolutional Network for Semantic Segmentation of Motion Capture Data
Noshaba Cheema, Somayeh Hosseini, Janis Sprenger +4
Semantic segmentation of motion capture sequences plays a key part in many data-driven motion synthesis frameworks. It is a preprocessing step in which long recordings of motion ca…