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of 4
pro vyhledávání: '"Meng, Wenming"'
In advanced paradigms of autonomous driving, learning Bird's Eye View (BEV) representation from surrounding views is crucial for multi-task framework. However, existing methods based on depth estimation or camera-driven attention are not stable to ob
Externí odkaz:
http://arxiv.org/abs/2210.17252
Learning Bird's Eye View (BEV) representation from surrounding-view cameras is of great importance for autonomous driving. In this work, we propose a Geometry-guided Kernel Transformer (GKT), a novel 2D-to-BEV representation learning mechanism. GKT l
Externí odkaz:
http://arxiv.org/abs/2206.04584
In this work, we propose a novel deep online correction (DOC) framework for monocular visual odometry. The whole pipeline has two stages: First, depth maps and initial poses are obtained from convolutional neural networks (CNNs) trained in self-super
Externí odkaz:
http://arxiv.org/abs/2103.10029
Autor:
Zhang, Qian, Li, Jianjun, Yao, Meng, Song, Liangchen, Zhou, Helong, Li, Zhichao, Meng, Wenming, Zhang, Xuezhi, Wang, Guoli
In this paper, we propose a novel network design mechanism for efficient embedded computing. Inspired by the limited computing patterns, we propose to fix the number of channels in a group convolution, instead of the existing practice that fixing the
Externí odkaz:
http://arxiv.org/abs/1907.05653