From the 1 of 6 linked papers with an AI index.
6 papers
MobileSAM2: Lightweight Segment Anything for Spatial Intelligence
Kai Jiang, Jiaxing Huang, Jingyi Zhang +5
The paper introduces MobileSAM2, a lightweight version of the SAM2 segmentation model designed for mobile devices, using hypergraph-based knowledge distillation to transfer tempora…
PacGDC: Label-Efficient Generalizable Depth Completion with Projection Ambiguity and Consistency
Haotian Wang, Aoran Xiao, Xiaoqin Zhang +2
Generalizable depth completion enables the acquisition of dense metric depth maps for unseen environments, offering robust perception capabilities for various downstream tasks. How…
Foundation Models for Remote Sensing and Earth Observation: A Survey
Aoran Xiao, Weihao Xuan, Junjue Wang +4
Remote Sensing (RS) is a crucial technology for observing, monitoring, and interpreting our planet, with broad applications across geoscience, economics, humanitarian fields, etc.…
Segment Anything with Multiple Modalities
Aoran Xiao, Weihao Xuan, Heli Qi +3
Robust and accurate segmentation of scenes has become one core functionality in various visual recognition and navigation tasks. This has inspired the recent development of Segment…
CAT-SAM: Conditional Tuning for Few-Shot Adaptation of Segment Anything Model
Aoran Xiao, Weihao Xuan, Heli Qi +5
The recent Segment Anything Model (SAM) has demonstrated remarkable zero-shot capability and flexible geometric prompting in general image segmentation. However, SAM often struggle…
A Survey of Label-Efficient Deep Learning for 3D Point Clouds
Aoran Xiao, Xiaoqin Zhang, Ling Shao +1
In the past decade, deep neural networks have achieved significant progress in point cloud learning. However, collecting large-scale precisely-annotated training data is extremely…