7 citations · 7 across the 4 of their papers we have counts for
5 papers
Masked BRep Autoencoder via Hierarchical Graph Transformer
Yifei Li, Kang Wu, Wenming Wu +1
We introduce a novel self-supervised learning framework that automatically learns representations from input computer-aided design (CAD) models for downstream tasks, including part…
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
Yingying Zhang, Lixiang Ru, Kang Wu +4
The multi-modal remote sensing foundation model (MM-RSFM) has significantly advanced various Earth observation tasks, such as urban planning, environmental monitoring, and natural…
When Large Vision-Language Model Meets Large Remote Sensing Imagery: Coarse-to-Fine Text-Guided Token Pruning
Junwei Luo, Yingying Zhang, Xue Yang +5
Efficient vision-language understanding of large Remote Sensing Images (RSIs) is meaningful but challenging. Current Large Vision-Language Models (LVLMs) typically employ limited p…
Fine-Grained Scene Graph Generation via Sample-Level Bias Prediction
Yansheng Li, Tingzhu Wang, Kang Wu +3
Scene Graph Generation (SGG) aims to explore the relationships between objects in images and obtain scene summary graphs, thereby better serving downstream tasks. However, the long…
SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery
Xin Guo, Jiangwei Lao, Bo Dang +13
Prior studies on Remote Sensing Foundation Model (RSFM) reveal immense potential towards a generic model for Earth Observation. Nevertheless, these works primarily focus on a singl…