Mar 18, 2023 · To this end, we propose a 3D data augmentation approach termed Drive-3DAug, aiming at augmenting the driving scenes on camera in the 3D space.
We first utilize Neural Radiance Field (NeRF) to reconstruct the 3D models of background and foreground objects. Then, augmented driving scenes can be obtained ...
This approach is intended to conduct the editing process within a 3D space, allowing for flexible object manipulation. Additionally, we introduce a neural scene ...
Apr 17, 2024 · Abstract—Creating large LiDAR datasets with pixel-level la- beling poses significant challenges. While numerous data aug-.
Drivemlm: Aligning multi-modal large language models with behavioral planning states for autonomous driving ... 3d data augmentation for driving scenes on camera.
Groundtruth sampling adds additional objects to the current scene. These objects, i.e. the bounding box and its inner points, are previously collected in a ...
In autonomous driving, data augmentation is commonly used for improving 3D object detection. The most basic methods include insertion of copied objects and ...
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We propose a 3D data augmentation approach termed Drive-3DAug to augment the driving scenes on camera in the 3D space. Towards Capturing the Temporal ...
3D Data Augmentation for Driving Scenes on Camera ... The proposed data augmentation approach contributes to a gain of 1. 7% and 1. 4% in terms of detection ...
Annotating the LiDAR point cloud is crucial for deep learning-based 3D object detection tasks. Due to expen- sive labeling costs, data augmentation has been ...