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pro vyhledávání: '"Ferenczi, Bryce"'
Various works have aimed at combining the inference efficiency of recurrent models and training parallelism of multi-head attention for sequence modeling. However, most of these works focus on tasks with fixed-dimension observation spaces, such as in
Externí odkaz:
http://arxiv.org/abs/2410.08681
Creation and storage of datasets are often overlooked input costs in machine learning, as many datasets are simple image label pairs or plain text. However, datasets with more complex structures, such as those from the real time strategy game StarCra
Externí odkaz:
http://arxiv.org/abs/2410.08659
Publikováno v:
IEEE Robotics and Automation Letters 2024
This work introduces a novel and adaptable architecture designed for real-time occupancy forecasting that outperforms existing state-of-the-art models on the Waymo Open Motion Dataset in Soft IOU. The proposed model uses recursive latent state estima
Externí odkaz:
http://arxiv.org/abs/2306.08879
Autor:
Zhu, Tianyu, Ferenczi, Bryce, Purkait, Pulak, Drummond, Tom, Rezatofighi, Hamid, Hengel, Anton van den
Rotated bounding boxes drastically reduce output ambiguity of elongated objects, making it superior to axis-aligned bounding boxes. Despite the effectiveness, rotated detectors are not widely employed. Annotating rotated bounding boxes is such a labo
Externí odkaz:
http://arxiv.org/abs/2304.02199
Akademický článek
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