1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2024★ 1 cited
Point Cloud Understanding via Attention-Driven Contrastive Learning
Yi Wang, Jiaze Wang, Ziyu Guo +5
Recently Transformer-based models have advanced point cloud understanding by leveraging self-attention mechanisms, however, these methods often overlook latent information in less…
cs.CV2024
MM-Mixing: Multi-Modal Mixing Alignment for 3D Understanding
Jiaze Wang, Yi Wang, Ziyu Guo +5
We introduce MM-Mixing, a multi-modal mixing alignment framework for 3D understanding. MM-Mixing applies mixing-based methods to multi-modal data, preserving and optimizing cross-m…
cs.CV2023
Language-Assisted 3D Scene Understanding
Yanmin Wu, Qiankun Gao, Renrui Zhang +1
The scale and quality of point cloud datasets constrain the advancement of point cloud learning. Recently, with the development of multi-modal learning, the incorporation of domain…