70 citations · 280 across the 23 of their papers we have counts for
23 papers
CAGroup3D: Class-Aware Grouping for 3D Object Detection on Point Clouds
Haiyang Wang, Lihe Ding, Shaocong Dong +5
We present a novel two-stage fully sparse convolutional 3D object detection framework, named CAGroup3D. Our proposed method first generates some high-quality 3D proposals by levera…
Boosting 3D Object Detection via Object-Focused Image Fusion
Hao Yang, Chen Shi, Yihong Chen +1
3D object detection has achieved remarkable progress by taking point clouds as the only input. However, point clouds often suffer from incomplete geometric structures and the lack…
Voxel Field Fusion for 3D Object Detection
Yanwei Li, Xiaojuan Qi, Yukang Chen +4
In this work, we present a conceptually simple yet effective framework for cross-modality 3D object detection, named voxel field fusion. The proposed approach aims to maintain cros…
RBGNet: Ray-based Grouping for 3D Object Detection
Haiyang Wang, Shaoshuai Shi, Ze Yang +5
As a fundamental problem in computer vision, 3D object detection is experiencing rapid growth. To extract the point-wise features from the irregularly and sparsely distributed poin…
Multi-View Transformer for 3D Visual Grounding
Shijia Huang, Yilun Chen, Jiaya Jia +1
The 3D visual grounding task aims to ground a natural language description to the targeted object in a 3D scene, which is usually represented in 3D point clouds. Previous works stu…
Stratified Transformer for 3D Point Cloud Segmentation
Xin Lai, Jianhui Liu, Li Jiang +5
3D point cloud segmentation has made tremendous progress in recent years. Most current methods focus on aggregating local features, but fail to directly model long-range dependenci…