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List of multi-view fusion learning models proposed for remote sensing (RS) multi-view data. Extension from our JSTAR paper.

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Remote Sensing based Multi-view Models

List of multi-view fusion learning models proposed for remote sensing (RS) multi-view data. 📡 🌎 📡

This is a complementary source used in the following paper:

Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing Applications
Name Reference Description Code
MV CNN Xu et al. 2018 Feature-level fusion with 2D CNN. https://github.com/Hsuxu/Two-branch-CNN-Multisource-RS-classification << Not available
V-FuseNet Audebert et al. 2018 Dense fusion with 2D CNN and central model. https://github.com/nshaud/DeepNetsForEO
Multi3Net Rudner et al. 2019 Feature-level fusion with 2D CNN. https://github.com/FrontierDevelopmentLab/multi3net
UNet-CLSTM Rustowicz et al. 2019 Decision-level fusion with 2D CNN and convolutional-LSTM https://github.com/roserustowicz/crop-type-mapping
HRWN Zhao et al. 2020 Input-level fusion with 2D CNN and pixel graph constraints. https://github.com/xudongzhao461/HRWN
FusAtNet Mohla et al. 2020 Feature-level fusion with 2D CNN and cross attention. https://github.com/ShivamP1993/FusAtNet
LFMC from SAR Rao et al Input-level fusion with LSTM https://github.com/kkraoj/lfmc_from_sar
CCR-Net Wu et al. 2021 Feature-level fusion with 2D CNN and cross view-reconstruction. https://github.com/danfenghong/IEEE_TGRS_CCR-Net
MV PSE-TAE Ofori-Ampofo et al. 2021 Multiple fusion strategies with PSE-TAE. https://github.com/ellaampy/CropTypeMapping
MDL-RS Hong et al. 2021 Multiple fusion strategies with NN. https://github.com/danfenghong/IEEE_TGRS_MDL-RS
CMGFNet Hosseinpour et al. 2022 Dense fusion with 2D CNN and gated attention. https://github.com/hamidreza2015/CMGFNet-Building_Extraction
S2FL Hong et al. 2021 Feature-level fusion with feature contrains. https://github.com/danfenghong/ISPRS_S2FL
CFCNN He et al. 2021 Feature-level fusion with 2D and 1D CNN. https://github.com/SysuHe/MultiSourceData_CFCNN
MV NN Danilevicz et al. 2021 Feature-level fusion with tabular NN and 2D CNN. https://github.com/mdanilevicz/maize_early_yield_prediction
SEnSeI Francis et al. 2022 Sensor invariant model based on 2D CNN https://github.com/aliFrancis/SEnSeI
ASF2N Gao et al. 2022 Feature-level fusion with 2D CNN and attention. https://github.com/zhonghaocheng/ELSEVIER_IJAEOG_AS2F2N << Empty code
IP-CNN Zhang et al. 2022 Feature-level fusion with 2D CNN and view-reconstruction. https://github.com/HelloPiPi/IP-CNN-code
MV CNN Lu et al. 2022 Feature-level fusion with 2D CNN and adaptive attention. https://github.com/GeoX-Lab/UnifiedDL-UFZ-extraction
SE$^2$Net Fang et al. 2022 Feature-level fusion with 2D CNN. https://github.com/likyoo/Multimodal-Remote-Sensing-Toolkit
EndNet Hong et al. 2022 Feature-level fusion with 2D CNN and view-reconstruction. https://github.com/danfenghong/IEEE_GRSL_EndNet
MAHiDFNet Wang et al. 2022 Dense feature fusion with 2D CNN. https://github.com/SYFYN0317/-MAHiDFNet
AM$^3$Net Wang et al. 2022 Feature-level fusion with 2D CNN and cross attention. https://github.com/Cimy-wang/AM3Net_Multimodal_Data_Fusion
AMM-FuseNet Ma et al. 2022 Feature-level fusion with 2D CNN and attention. https://github.com/oktaykarakus/ReSIF/tree/main/AMM-FuseNet
MCANet Li et al. 2022 Dense fusion with 2D CNN and cross attention. https://github.com/yisun98/SOLC
ChangeFormer Bandara et al. 2022 Dense fusion with transformer and attention. https://github.com/wgcban/ChangeFormer
CMAFF Qingyun et al. 2022 Dense fusion with 2D CNN and cross attention. https://github.com/DocF/CMAFF
OmbriaNet Drakonakis et al. 2022 Feature fusion with 2D CNN and skip-connections https://github.com/geodrak/OMBRIA
DCSA-Net Wang et al. 2022 Hybrid fusion with 2D CNN and attention. https://github.com/Julia90/DCSA-Net
Siamese U-Net Cummings et al. 2022 Dense fusion with 2D CNN and skip-connections https://github.com/solcummings/earthvision2021-weakly-supervised
SatViT Fuller et al. Input-level fusion with ViT (with self-supervised training) https://github.com/antofuller/SatViT
ELECTS Russwurm et al. 2023 Input-level fusion with LSTM. https://github.com/marccoru/elects
MV CNN Ferrari et al. 2023 Multiple fusion strategies with 2D CNN (encoder-decoder) https://github.com/felferrari/deforestation-from-data-fusion
AFCF3D-Net Ye et al. 2023 Input-level fusion with 3D CNN. https://github.com/wm-Githuber/AFCF3D-Net
UnCRtainTS Ebel et al 2023 Input fusion with 2D CNN and attention. https://github.com/PatrickTUM/UnCRtainTS
MFT Roy et al. 2023 Feature-level fusion with transformer modules (one source - LIDAR- is used as a query over the main source - optical) https://github.com/AnkurDeria/MFT
OOD Fusion Gawlikowski et al. 2023 Input-level, Feature-level, and Decision-level fusion with CNN and weighted average aggregation https://github.com/JakobCode/OOD_DataFusion
PRESTO Tseng et al. 2023 Input-level fusion with transformer modules (self-supervised pretraining) https://github.com/nasaharvest/presto
Cross-HL Roy et al. 2023 Feature-level fusion with directed attention in transformer layers https://github.com/AtriSukul1508/Cross-HL
SCT Fusion Hoffman et al. 2023 Dense fusion with tranformer layers and class tokens in all https://git.tu-berlin.de/rsim/sct-fusion
MMST-ViT Lin et al. 2023 Feature-level fusion with transformer layers https://github.com/fudong03/MMST-ViT
DiffusionSat Khanna et al. 2023 Multi-modal diffusion generative model https://github.com/samar-khanna/DiffusionSat
SSL4EO-S12 Wang et al. 2024 Self-supervised model https://github.com/zhu-xlab/SSL4EO-S12
EarthGPT Zhang et al. 2024 Feature-level fusion with transformer layers https://github.com/wivizhang/EarthGPT
ContextFormer Benson et al. 2024 Feature-level fusion with transformer https://github.com/vitusbenson/greenearthnet
SEnSeIv2 Francis 2024 Sensor-invariant model https://github.com/aliFrancis/SEnSeIv2
OmniSat Astruc et al. 2024 Feature-level fusion with transformer layers and pre-training https://github.com/gastruc/OmniSat

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Some abbrevations

Abbrevation name
CNN convolutional neural network
LSTM long-short term memory
NN neural network
PSE-TAE pixel set encoder - temporal attention encoder

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List of multi-view fusion learning models proposed for remote sensing (RS) multi-view data. Extension from our JSTAR paper.

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