F2BEV: Bird's Eye View Generation from Surround-View Fisheye Camera Images for Automated Driving

• URL: http://arxiv.org/abs/2303.03651v2
• Date: Tue, 1 Aug 2023 19:41:49 GMT
• Title: F2BEV: Bird's Eye View Generation from Surround-View Fisheye Camera Images for Automated Driving
• Authors: Ekta U. Samani, Feng Tao, Harshavardhan R. Dasari, Sihao Ding, Ashis G. Banerjee
• Abstract summary: We introduce a baseline, F2BEV, to generate BEV height maps and BEV semantic segmentation maps from fisheye images. F2BEV consists of a distortion-aware spatial cross attention module for querying and consolidating spatial information. We evaluate single-task and multi-task variants of F2BEV on our synthetic FB-SSEM dataset.
• Score: 3.286961611175469
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Bird's Eye View (BEV) representations are tremendously useful for perception-related automated driving tasks. However, generating BEVs from surround-view fisheye camera images is challenging due to the strong distortions introduced by such wide-angle lenses. We take the first step in addressing this challenge and introduce a baseline, F2BEV, to generate discretized BEV height maps and BEV semantic segmentation maps from fisheye images. F2BEV consists of a distortion-aware spatial cross attention module for querying and consolidating spatial information from fisheye image features in a transformer-style architecture followed by a task-specific head. We evaluate single-task and multi-task variants of F2BEV on our synthetic FB-SSEM dataset, all of which generate better BEV height and segmentation maps (in terms of the IoU) than a state-of-the-art BEV generation method operating on undistorted fisheye images. We also demonstrate discretized height map generation from real-world fisheye images using F2BEV. Our dataset is publicly available at https://github.com/volvo-cars/FB-SSEM-dataset

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