The emerging topic of cross-source point cloud (CSPC) registration has attracted increasing
attention with the fast development background of 3D sensor technologies. Different from the …

Large language models have emerged as a promising approach towards achieving general-
purpose AI agents. The thriving open-source LLM community has greatly accelerated the …

Pre-training across 3D vision and language remains under development because of limited
training data. Recent works attempt to transfer vision-language (VL) pre-training methods to …

The use of pretrained backbones with fine-tuning has been successful for 2D vision and
natural language processing tasks, showing advantages over task-specific networks. In this …

Scaling up representations for images or text has been extensively investigated in the past
few years and has led to revolutions in learning vision and language. However, scalable …

Pre-trained point cloud models have found extensive applications in 3D understanding tasks
like object classification and part segmentation. However, the prevailing strategy of full fine …

Pre-training a model and then fine-tuning it on downstream tasks has demonstrated
significant success in the 2D image and NLP domains. However due to the unordered and …

The remarkable potential of multi-modal large language models (MLLMs) in comprehending
both vision and language information has been widely acknowledged. However, the scarcity …

Point cloud data has been extensively studied due to its compact form and flexibility in
representing complex 3D structures. The ability of point cloud data to accurately capture and …

Contrasting Language-image pertaining (CLIP) has recently shown promising open-world
and few-shot performance on 2D image-based recognition tasks. However, the transferred …