RobustLoc: Robust Camera Pose Regression in Challenging Driving Environments

Camera relocalization has various applications in autonomous driving. Previous camera pose regression models consider only ideal scenarios where there is little environmental perturbation. To deal with challenging driving environments that may have changing seasons, weather, illumination, and the presence of unstable objects, we propose RobustLoc, which derives its robustness against perturbations from neural differential equations. Our model uses a convolutional neural network to extract feature maps from multi-view images, a robust neural differential equation diffusion block module to diffuse information interactively, and a branched pose decoder with multi-layer training to estimate the vehicle poses. Experiments demonstrate that RobustLoc surpasses current state-of-the-art camera pose regression models and achieves robust performance in various environments. Our code is released at: https://github.com/sijieaaa/RobustLoc

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Task Dataset Model Metric Name Metric Value Global Rank Benchmark
camera absolute pose regression 4Seasons Business Campus RobustLoc Mean Translation/Rotation Error (m/degree) 4.28 / 2.04 # 1
camera absolute pose regression 4Seasons Neighborhood RobustLoc Mean Translation/Rotation Error (m/degree) 1.36 / 0.83 # 1
camera absolute pose regression 4Seasons Old Town RobustLoc Mean Translation/Rotation Error (m/degree) 21.65 / 2.41 # 1
Visual Localization Oxford RobotCar Full RobustLoc Mean Translation Error 9.37 # 1
Camera Localization Oxford RobotCar Full RobustLoc Mean Translation Error 9.37 # 1
Mean Rotation Error 2.47 # 1
camera absolute pose regression Oxford RobotCar Full RobustLoc Mean Translation/Rotation Error (m/degree) 9.37 / 2.47 # 1
Median Translation/Rotation Error (m/degree) 5.93 / 1.06 # 1
camera absolute pose regression Oxford RobotCar Loop (cross-day) RobustLoc Mean Translation/Rotation Error (m/degree) 4.68 / 2.67 # 1
Median Translation/Rotation Error (m/degree) 3.70 / 1.50 # 1
camera absolute pose regression Oxford RobotCar Loop (within-day) RobustLoc Mean Translation/Rotation Error (m/degree) 2.49 / 1.40 # 1
Median Translation/Rotation Error (m/degree) 1.97 / 0.84 # 1

Methods