OpenAnnotate3D: Open-Vocabulary Auto-Labeling System for Multi-modal 3D Data

no code implementations • 20 Oct 2023 • Yijie Zhou, Likun Cai, Xianhui Cheng, Zhongxue Gan, xiangyang xue, Wenchao Ding

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.

Autonomous Driving

Understanding Depth Map Progressively: Adaptive Distance Interval Separation for Monocular 3d Object Detection

no code implementations • 19 Jun 2023 • Xianhui Cheng, Shoumeng Qiu, Zhikang Zou, Jian Pu, xiangyang xue

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.

Depth Estimation Monocular 3D Object Detection +1

The Devil is in the Task: Exploiting Reciprocal Appearance-Localization Features for Monocular 3D Object Detection

no code implementations • ICCV 2021 • Zhikang Zou, Xiaoqing Ye, Liang Du, Xianhui Cheng, Xiao Tan, Li Zhang, Jianfeng Feng, xiangyang xue, Errui Ding

Low-cost monocular 3D object detection plays a fundamental role in autonomous driving, whereas its accuracy is still far from satisfactory.

Autonomous Driving Monocular 3D Object Detection +4