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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. :satellite: :earth_americas: :satellite:

This is a complementary source used in the following paper:

Common Practices and Taxonomy in Deep Multi-view Fusion for Remote Sensing Applications
NameReferenceDescriptionCode
MV CNNXu et al. 2018Feature-level fusion with 2D CNN.https://github.com/Hsuxu/Two-branch-CNN-Multisource-RS-classification << Not available
V-FuseNetAudebert et al. 2018Dense fusion with 2D CNN and central model.https://github.com/nshaud/DeepNetsForEO
Multi3NetRudner et al. 2019Feature-level fusion with 2D CNN.https://github.com/FrontierDevelopmentLab/multi3net
UNet-CLSTMRustowicz et al. 2019Decision-level fusion with 2D CNN and convolutional-LSTMhttps://github.com/roserustowicz/crop-type-mapping
HRWNZhao et al. 2020Input-level fusion with 2D CNN and pixel graph constraints.https://github.com/xudongzhao461/HRWN
FusAtNetMohla et al. 2020Feature-level fusion with 2D CNN and cross attention.https://github.com/ShivamP1993/FusAtNet
LFMC from SARRao et alInput-level fusion with LSTMhttps://github.com/kkraoj/lfmc_from_sar
CCR-NetWu et al. 2021Feature-level fusion with 2D CNN and cross view-reconstruction.https://github.com/danfenghong/IEEE_TGRS_CCR-Net
MV PSE-TAEOfori-Ampofo et al. 2021Multiple fusion strategies with PSE-TAE.https://github.com/ellaampy/CropTypeMapping
MDL-RSHong et al. 2021Multiple fusion strategies with NN.https://github.com/danfenghong/IEEE_TGRS_MDL-RS
CMGFNetHosseinpour et al. 2022Dense fusion with 2D CNN and gated attention.https://github.com/hamidreza2015/CMGFNet-Building_Extraction
S2FLHong et al. 2021Feature-level fusion with feature contrains.https://github.com/danfenghong/ISPRS_S2FL
CFCNNHe et al. 2021Feature-level fusion with 2D and 1D CNN.https://github.com/SysuHe/MultiSourceData_CFCNN
MV NNDanilevicz et al. 2021Feature-level fusion with tabular NN and 2D CNN.https://github.com/mdanilevicz/maize_early_yield_prediction
SEnSeIFrancis et al. 2022Sensor invariant model based on 2D CNNhttps://github.com/aliFrancis/SEnSeI
ASF2NGao et al. 2022Feature-level fusion with 2D CNN and attention.https://github.com/zhonghaocheng/ELSEVIER_IJAEOG_AS2F2N << Empty code
IP-CNNZhang et al. 2022Feature-level fusion with 2D CNN and view-reconstruction.https://github.com/HelloPiPi/IP-CNN-code
MV CNNLu et al. 2022Feature-level fusion with 2D CNN and adaptive attention.https://github.com/GeoX-Lab/UnifiedDL-UFZ-extraction
SE$^2$NetFang et al. 2022Feature-level fusion with 2D CNN.https://github.com/likyoo/Multimodal-Remote-Sensing-Toolkit
EndNetHong et al. 2022Feature-level fusion with 2D CNN and view-reconstruction.https://github.com/danfenghong/IEEE_GRSL_EndNet
MAHiDFNetWang et al. 2022Dense feature fusion with 2D CNN.https://github.com/SYFYN0317/-MAHiDFNet
AM$^3$NetWang et al. 2022Feature-level fusion with 2D CNN and cross attention.https://github.com/Cimy-wang/AM3Net_Multimodal_Data_Fusion
AMM-FuseNetMa et al. 2022Feature-level fusion with 2D CNN and attention.https://github.com/oktaykarakus/ReSIF/tree/main/AMM-FuseNet
MCANetLi et al. 2022Dense fusion with 2D CNN and cross attention.https://github.com/yisun98/SOLC
ChangeFormerBandara et al. 2022Dense fusion with transformer and attention.https://github.com/wgcban/ChangeFormer
CMAFFQingyun et al. 2022Dense fusion with 2D CNN and cross attention.https://github.com/DocF/CMAFF
OmbriaNetDrakonakis et al. 2022Feature fusion with 2D CNN and skip-connectionshttps://github.com/geodrak/OMBRIA
DCSA-NetWang et al. 2022Hybrid fusion with 2D CNN and attention.https://github.com/Julia90/DCSA-Net
Siamese U-NetCummings et al. 2022Dense fusion with 2D CNN and skip-connectionshttps://github.com/solcummings/earthvision2021-weakly-supervised
SatViTFuller et al.Input-level fusion with ViT (with self-supervised training)https://github.com/antofuller/SatViT
ELECTSRusswurm et al. 2023Input-level fusion with LSTM.https://github.com/marccoru/elects
MV CNNFerrari et al. 2023Multiple fusion strategies with 2D CNN (encoder-decoder)https://github.com/felferrari/deforestation-from-data-fusion
AFCF3D-NetYe et al. 2023Input-level fusion with 3D CNN.https://github.com/wm-Githuber/AFCF3D-Net
UnCRtainTSEbel et al 2023Input fusion with 2D CNN and attention.https://github.com/PatrickTUM/UnCRtainTS
MFTRoy et al. 2023Feature-level fusion with transformer modules (one source - LIDAR- is used as a query over the main source - optical)https://github.com/AnkurDeria/MFT
OOD FusionGawlikowski et al. 2023Input-level, Feature-level, and Decision-level fusion with CNN and weighted average aggregationhttps://github.com/JakobCode/OOD_DataFusion
PRESTOTseng et al. 2023Input-level fusion with transformer modules (self-supervised pretraining)https://github.com/nasaharvest/presto
Cross-HLRoy et al. 2023Feature-level fusion with directed attention in transformer layershttps://github.com/AtriSukul1508/Cross-HL
SCT FusionHoffman et al. 2023Dense fusion with tranformer layers and class tokens in allhttps://git.tu-berlin.de/rsim/sct-fusion
MMST-ViTLin et al. 2023Feature-level fusion with transformer layershttps://github.com/fudong03/MMST-ViT
DiffusionSatKhanna et al. 2023Multi-modal diffusion generative modelhttps://github.com/samar-khanna/DiffusionSat
SSL4EO-S12Wang et al. 2024Self-supervised modelhttps://github.com/zhu-xlab/SSL4EO-S12
EarthGPTZhang et al. 2024Feature-level fusion with transformer layershttps://github.com/wivizhang/EarthGPT
ContextFormerBenson et al. 2024Feature-level fusion with transformerhttps://github.com/vitusbenson/greenearthnet
SEnSeIv2Francis 2024Sensor-invariant modelhttps://github.com/aliFrancis/SEnSeIv2
OmniSatAstruc et al. 2024Feature-level fusion with transformer layers and pre-traininghttps://github.com/gastruc/OmniSat

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Some abbrevations

Abbrevationname
CNNconvolutional neural network
LSTMlong-short term memory
NNneural network
PSE-TAEpixel set encoder - temporal attention encoder