CNN based semantic segmentation for urban traffic scenes using fisheye camera

By Liuyuan Deng, Ming Yang, Yeqiang Qian, Chunxiang Wang, Bing Wang. 2017

111 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

WoodScape: A Multi-Task, Multi-Camera Fisheye Dataset for Autonomous Driving (2019, neutral): “Semantic segmentation networks for autonomous driving [47] have been successfully trained directly on fisheye images in [12, 45].”
Datasets for face and object detection in fisheye images (2019, methodology): “[4] is based on equidistant projection and requires the user to specify the focal length of the camera.”
CNN-based Fisheye Image Real-Time Semantic Segmentation (2018, methodology): “For the remapping process we initially use an arbitrary focal length of f0 = 159 as in [1], but additionally a new data augmentation strategy is tested.”
Is Context-Aware CNN Ready for the Surroundings? Panoramic Semantic Segmentation in the Wild (2021, background): “Early vision-based surrounding perception systems leveraged fisheye sensors [40] that were often horizontally arranged in an array [41], [42].”