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20232026
most citedCDMamba: Incorporating Local Clues into Mamba for Remote Sensing Image Binary Change Detection

18 citations · 33 across the 12 of their papers we have counts for

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Showing 2024 · cs.CVShow all

6 papers · 2 filters

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024★ 18 cited

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…

cs.CV2024

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…

cs.CV2024★ 4 cited

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…

cs.CV2024

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…