Getting better placement of objects in a scene
Getting better placement of objects in a scene
SBEVNet: End-to-End Deep Stereo Layout Estimation
arXiv paper abstract https://arxiv.org/abs/2105.11705v1
arXiv PDF paper https://arxiv.org/pdf/2105.11705v1.pdf
... introduce the Stereo Bird's Eye ViewNetwork (SBEVNet), a novel supervised end-to-end framework for estimation of bird's eye view layout from a pair of stereo images.
Although our network reuses some of the building blocks from the state-of-the-art deep learning networks for disparity estimation, we show that explicit depth estimation is neither sufficient nor necessary.
Instead, the learning of a good internal bird's eye view feature representation is effective for layout estimation.
... We demonstrate our approach on two datasets:the KITTI dataset and a synthetically generated dataset from the CARLA simulator.
For both of these datasets, we establish state-of-the-art performance compared to baseline techniques.
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