In this paper, we propose a novel self-distillation framework and firstly use it for robust LiDAR semantic segmentation in autonomous driving. The proposed.
Oct 20, 2022 · We propose a new and effective self-distillation framework with our new Test-Time Augmentation (TTA) and Transformer based Voxel Feature Encoder (TransVFE)
Nov 21, 2024 · We propose a new and effective self-distillation framework with our new Test-Time Augmentation (TTA) and Transformer based Voxel Feature ...
We propose a new and effective self-distillation framework with our new Test-Time Augmentation (TTA) and Transformer based Voxel Feature Encoder (TransVFE) for ...
[PDF] Supplementary Material for Self-Distillation for Robust LiDAR ...
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Robustness test on SemanticKITTI validation set for each components under more types of disturbances: 1) clean point cloud, 2) add point-wise random noise ( ...
[2022-07-04] Our LiDAR-only method SDSeg3D (Self-Distillation for Robust LiDAR Semantic Segmentation in Autonomous Driving) is accepted as a poster paper at ...
Extensive experiments on autonomous driving datasets demonstrate the ability of the image-to-Lidar distillation strategy to produce 3D representations that ...
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What is semantic segmentation for self driving cars?
What is LiDAR in autonomous driving?
Self-distillation for robust lidar semantic segmentation in autonomous driving. J Li, H Dai, Y Ding. European conference on computer vision, 659-676, 2022. 31 ...
Sep 1, 2024 · However, distilling 3D representations for autonomous driving datasets presents challenges like self-similarity, class imbalance, and point ...
Segmenting or detecting objects in sparse Lidar point clouds are two important tasks in autonomous driving to allow a vehicle to act safely in its 3D ...