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Adaptive gaussian mixture trajectory model for physical model control using motion capture data., , , , , , and . I3D, page 12:1-12:8. ACM, (2019)Dilated Temporal Fully-Convolutional Network for Semantic Segmentation of Motion Capture Data., , , , , , and . Symposium on Computer Animation (Posters), page 5-6. Eurographics Association, (2018)Toward a Methodology for Training with Synthetic Data on the Example of Pedestrian Detection in a Frame-by-Frame Semantic Segmentation Task., , and . SEFAIAS@ICSE, page 31-34. ACM, (2018)Motion Data and Model Management for Applied Statistical Motion Synthesis., , , , , , , , , and 2 other author(s). STAG, page 79-88. Eurographics Association, (2019)Natural Posture Blending Using Deep Neural Networks., , , and . MIG, page 2:1-2:6. ACM, (2019)Capturing Subtle Motion Differences of Pedestrian Street Crossings., , , , and . CASA, page 29-32. ACM, (2019)Fine-Grained Semantic Segmentation of Motion Capture Data using Dilated Temporal Fully-Convolutional Networks., , , , , , and . Eurographics (Short Papers), page 69-72. Eurographics Association, (2019)Stylistic Locomotion Modeling and Synthesis using Variational Generative Models., , , , and . MIG, page 32:1-32:10. ACM, (2019)Cross-Cultural Behavior Analysis of Street-Crossing Pedestrians in Japan and Germany., , , , , and . IV, page 1-7. IEEE, (2023)Pedestrian Behavior in Japan and Germany: A Review., , , , and . IV, page 1529-1536. IEEE, (2021)