10 papers
Vector Map as Language: Toward Unified Remote Sensing Vector Mapping
Yinglong Yan, Yunkai Yang, Haoyi Wang +7
Remote sensing vector mapping aims to generate structured maps of geospatial entities, such as buildings, roads, and water bodies, from remote sensing imagery. In practice, vector…
High-Energy Concentration for Federated Learning in Frequency Domain
Haozhi Shi, Weiying Xie, Hangyu Ye +4
Federated Learning (FL) presents significant potential for collaborative optimization without data sharing. Since synthetic data is sent to the server, leveraging the popular conce…
HeteroTune: Efficient Federated Learning for Large Heterogeneous Models
Ruofan Jia, Weiying Xie, Jie Lei +3
While large pre-trained models have achieved impressive performance across AI tasks, their deployment in privacy-sensitive and distributed environments remains challenging. Federat…
FusionSAM: Visual Multi-Modal Learning with Segment Anything
Daixun Li, Weiying Xie, Mingxiang Cao +5
Multimodal image fusion and semantic segmentation are critical for autonomous driving. Despite advancements, current models often struggle with segmenting densely packed elements d…
Weakly Supervised Point Cloud Segmentation via Conservative Propagation of Scene-level Labels
Shaobo Xia, Jun Yue, Kacper Kania +4
We propose a weakly supervised semantic segmentation method for point clouds that predicts "per-point" labels from just "whole-scene" annotations. The key challenge here is the dis…
Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectives
Yidan Liu, Jun Yue, Shaobo Xia +3
As a newly emerging advance in deep generative models, diffusion models have achieved state-of-the-art results in many fields, including computer vision, natural language processin…