Search Results for author:
Found 3 papers, 1 papers with code
OpenAnnotate3D: Open-Vocabulary Auto-Labeling System for Multi-modal 3D Data
In the era of big data and large models, automatic annotating functions for multi-modal data are of great significance for real-world AI-driven applications, such as autonomous driving and embodied AI.
Understanding Depth Map Progressively: Adaptive Distance Interval Separation for Monocular 3d Object Detection
In this paper, we propose a framework named the Adaptive Distance Interval Separation Network (ADISN) that adopts a novel perspective on understanding depth maps, as a form that lies between LiDAR and images.
The Devil is in the Task: Exploiting Reciprocal Appearance-Localization Features for Monocular 3D Object Detection
Low-cost monocular 3D object detection plays a fundamental role in autonomous driving, whereas its accuracy is still far from satisfactory.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
