Titlebook: Ver?nderungen in den japanischen Wertsch?pfungsstrukturen; Die Beispiele Maschi Ute Ro?mann Book 2003 Deutscher Universit?ts-Verlag/GWV Fac

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Ute Ro?mannVTs to a large extent. Therefore, our locality guidance approach is very simple and efficient, and can serve as a basic performance enhancement method for VTs on tiny datasets. Extensive experiments demonstrate that our method can significantly improve VTs when training from scratch on tiny datasets

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also achieve performance comparable to prior work that uses a parametric human body model and temporal feature aggregation. Our experiments show that a majority of errors in prior work stem from an inappropriate choice of spatial encoding and thus we suggest a new direction for high-fidelity image-

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, in the literature, most of the methods focus on devising sophisticated matching modules at point-level, while overlooking the rich spatial context information of points. To this end, we propose .ontext-.atching-Guided .ransformer (.), a Siamese tracking paradigm for 3D single object tracking. In t

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Ute Ro?mann desirable due to the heavy burden of collecting abundant dense annotations for the model training. However, existing methods remain challenging to accurately segment 3D point clouds since limited annotated data may lead to insufficient guidance for label propagation to unlabeled data. Considering t

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Ute Ro?mannrsation. As the indispensable complement to talking heads generation, listening head generation has seldomly been studied in literature. Automatically synthesizing listening behavior that actively responds to a talking head, is critical to applications such as digital human, virtual agents and socia

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