2 citations · 2 across the 1 of their papers we have counts for
3 papers
cs.CV2023
OpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance Segmentation
Zhening Huang, Xiaoyang Wu, Xi Chen +3
In this work, we introduce OpenIns3D, a new 3D-input-only framework for 3D open-vocabulary scene understanding. The OpenIns3D framework employs a "Mask-Snap-Lookup" scheme. The "Ma…
cs.CV2023
Towards Large-scale 3D Representation Learning with Multi-dataset Point Prompt Training
Xiaoyang Wu, Zhuotao Tian, Xin Wen +4
The rapid advancement of deep learning models often attributes to their ability to leverage massive training data. In contrast, such privilege has not yet fully benefited 3D deep l…
cs.CV2023★ 2 cited
MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds
Jiahui Liu, Chirui Chang, Jianhui Liu +3
3D semantic segmentation on multi-scan large-scale point clouds plays an important role in autonomous systems. Unlike the single-scan-based semantic segmentation task, this task re…