19 citations · 43 across the 7 of their papers we have counts for
7 papers
Spatial Pruned Sparse Convolution for Efficient 3D Object Detection
Jianhui Liu, Yukang Chen, Xiaoqing Ye +3
3D scenes are dominated by a large number of background points, which is redundant for the detection task that mainly needs to focus on foreground objects. In this paper, we analyz…
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…
Focal Sparse Convolutional Networks for 3D Object Detection
Yukang Chen, Yanwei Li, Xiangyu Zhang +2
Non-uniformed 3D sparse data, e.g., point clouds or voxels in different spatial positions, make contribution to the task of 3D object detection in different ways. Existing basic co…
Multi-Scale Aligned Distillation for Low-Resolution Detection
Lu Qi, Jason Kuen, Jiuxiang Gu +5
In instance-level detection tasks (e.g., object detection), reducing input resolution is an easy option to improve runtime efficiency. However, this option traditionally hurts the…
ICM-3D: Instantiated Category Modeling for 3D Instance Segmentation
Ruihang Chu, Yukang Chen, Tao Kong +2
Separating 3D point clouds into individual instances is an important task for 3D vision. It is challenging due to the unknown and varying number of instances in a scene. Existing d…
Single-DARTS: Towards Stable Architecture Search
Pengfei Hou, Ying Jin, Yukang Chen
Differentiable architecture search (DARTS) marks a milestone in Neural Architecture Search (NAS), boasting simplicity and small search costs. However, DARTS still suffers from freq…