18 citations · 33 across the 12 of their papers we have counts for
8 papers · 1 filter
Efficient Semantic Splatting for Remote Sensing Multi-view Segmentation
Zipeng Qi, Hao Chen, Haotian Zhang +2
In this paper, we propose a novel semantic splatting approach based on Gaussian Splatting to achieve efficient and low-latency. Our method projects the RGB attributes and semantic…
MambaDS: Near-Surface Meteorological Field Downscaling with Topography Constrained Selective State Space Modeling
Zili Liu, Hao Chen, Lei Bai +4
In an era of frequent extreme weather and global warming, obtaining precise, fine-grained near-surface weather forecasts is increasingly essential for human activities. Downscaling…
Open-CD: A Comprehensive Toolbox for Change Detection
Kaiyu Li, Jiawei Jiang, Andrea Codegoni +13
We present Open-CD, a change detection toolbox that contains a rich set of change detection methods as well as related components and modules. The toolbox started from a series of…
CDMamba: Incorporating Local Clues into Mamba for Remote Sensing Image Binary Change Detection
Haotian Zhang, Keyan Chen, Chenyang Liu +3
Recently, the Mamba architecture based on state space models has demonstrated remarkable performance in a series of natural language processing tasks and has been rapidly applied t…
Multi-view Remote Sensing Image Segmentation With SAM priors
Zipeng Qi, Chenyang Liu, Zili Liu +4
Multi-view segmentation in Remote Sensing (RS) seeks to segment images from diverse perspectives within a scene. Recent methods leverage 3D information extracted from an Implicit N…
Observation-Guided Meteorological Field Downscaling at Station Scale: A Benchmark and a New Method
Zili Liu, Hao Chen, Lei Bai +6
Downscaling (DS) of meteorological variables involves obtaining high-resolution states from low-resolution meteorological fields and is an important task in weather forecasting. Pr…
Learning to detect cloud and snow in remote sensing images from noisy labels
Zili Liu, Hao Chen, Wenyuan Li +5
Detecting clouds and snow in remote sensing images is an essential preprocessing task for remote sensing imagery. Previous works draw inspiration from semantic segmentation models…
DeepPhysiNet: Bridging Deep Learning and Atmospheric Physics for Accurate and Continuous Weather Modeling
Wenyuan Li, Zili Liu, Keyan Chen +4
Accurate weather forecasting holds significant importance to human activities. Currently, there are two paradigms for weather forecasting: Numerical Weather Prediction (NWP) and De…