期刊
1. IEEE Transactions on Geoscience and Remote Sensing
2. ISPRS Journal of Photogrammetry and Remote Sensing（Elsevier）
3. Remote Sensing of Environment（Elsevier）
1. GeoChat: Grounded Large Vision-Language Model for Remote Sensing（CVPR2024）
code：https://github.com/mbzuai-oryx/geochat
https://github.com/mbzuai-oryx/geochat
2. SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery（CVPR2024）
code:未公开
3. 3D Building Reconstruction from Monocular Remote Sensing Images with Multi-level Supervisions（CVPR2024）
code: https://github.com/opendatalab/MLS-BRNhttps://github.com/opendatalab/MLS-BRN
4. Poly Kernel Inception Network for Remote Sensing Detection（CVPR2024）
5. Content-Adaptive Non-Local Convolution for Remote Sensing Pansharpening（CVPR2024）
code:https://github.com/duanyll/CANConvhttps://github.com/duanyll/CANConv
6. Rotated Multi-Scale Interaction Network for Referring Remote Sensing Image Segmentation（CVPR2024）
code：http://https: //github.com/Lsan2401/RMSINhttp://https//github.com/Lsan2401/RMSIN
7. Bridging Remote Sensors with Multisensor Geospatial Foundation Models（CVPR2024）
8. S2MAE: A Spatial-Spectral Pretraining Foundation Model for Spectral Remote Sensing Data（CVPR2024）
code：未公开
9. Rethinking Transformers Pre-training for Multi-Spectral Satellite Imagery（CVPR2024）
code:https://github.com/techmn/satmae_pphttps://github.com/techmn/satmae_pp
10. Aerial Lifting: Neural Urban Semantic and Building Instance Lifting from Aerial Imagery（CVPR2024）
code:https://github.com/zyqz97/Aerial_liftinghttps://github.com/zyqz97/Aerial_lifting
11. Sat2Scene: 3D Urban Scene Generation from Satellite Images with Diffusion（CVPR2024）
code:未公开
12. SG-BEV: Satellite-Guided BEV Fusion for Cross-View Semantic Segmentation（CVPR2024）
code:http://https: //github.com/yejy53/SG-BEVhttp://https//github.com/yejy53/SG-BEV
13. WildlifeMapper: Aerial Image Analysis for Multi-Species Detection and Identification（CVPR2024）
code:https://github.com/UCSB-VRL/WildlifeMapperhttps://github.com/UCSB-VRL/WildlifeMapper
14. Multiview Aerial Visual Recognition (MAVREC): Can Multi-view Improve Aerial Visual Perception?（CVPR2024）
15. Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans（CVPR2024）
16. Multiplane Prior Guided Few-Shot Aerial Scene Rendering（CVPR2024）
code:未公开
17. SatSynth: Augmenting Image-Mask Pairs through Diffusion Models for Aerial Semantic Segmentation（CVPR2024）
code:未公开
18. EarthLoc: Astronaut Photography Localization by Indexing Earth from Space（CVPR2024）
19. ShadowSense: Unsupervised Domain Adaptation and Feature Fusion for Shadow-Agnostic Tree Crown Detection from RGB-Thermal Drone Imagery （WACV2024）
paper:https://openaccess.thecvf.com/content/WACV2024/papers/Kapil_ShadowSense_Unsupervised_Domain_Adaptation_and_Feature_Fusion_for_Shadow-Agnostic_Tree_WACV_2024_paper.pdfhttps://openaccess.thecvf.com/content/WACV2024/papers/Kapil_ShadowSense_Unsupervised_Domain_Adaptation_and_Feature_Fusion_for_Shadow-Agnostic_Tree_WACV_2024_paper.pdfcode:GitHub - rudrakshkapil/ShadowSense: Official code implementation for WACV 2024 paper "ShadowSense: Unsupervised Domain Adaptation and Feature Fusion for Shadow-Agnostic Tree Crown Detection from RGB-Thermal Drone Imagery"Official code implementation for WACV 2024 paper "ShadowSense: Unsupervised Domain Adaptation and Feature Fusion for Shadow-Agnostic Tree Crown Detection from RGB-Thermal Drone Imagery" - rudrakshkapil/ShadowSensehttps://github.com/rudrakshkapil/ShadowSense
20. Vision Transformer for Multispectral Satellite Imagery: Advancing Landcover Classification*（WACV2024）
21. UOW-Vessel: A Benchmark Dataset of High-Resolution Optical Satellite Images for Vessel Detection and Segmentation（WACV2024）
paper:https://openaccess.thecvf.com/content/WACV2024/papers/Bui_UOW-Vessel_A_Benchmark_Dataset_of_High-Resolution_Optical_Satellite_Images_for_WACV_2024_paper.pdfhttps://openaccess.thecvf.com/content/WACV2024/papers/Bui_UOW-Vessel_A_Benchmark_Dataset_of_High-Resolution_Optical_Satellite_Images_for_WACV_2024_paper.pdfcode:University of Wollongong – UOW - A world-class UniversityUOW is one of the world's top modern universities, offering excellence in teaching, learning, and research, and an unparalleled student experience.https://documents.uow.edu.au/%E2%88%BCphung/UOW-Vessel.html
22. SICKLE: A Multi-Sensor Satellite Imagery Dataset Annotated with Multiple Key Cropping Parameters（WACV2024）
paper:https://openaccess.thecvf.com/content/WACV2024/papers/Sani_SICKLE_A_Multi-Sensor_Satellite_Imagery_Dataset_Annotated_With_Multiple_Key_WACV_2024_paper.pdfhttps://openaccess.thecvf.com/content/WACV2024/papers/Sani_SICKLE_A_Multi-Sensor_Satellite_Imagery_Dataset_Annotated_With_Multiple_Key_WACV_2024_paper.pdfcode:https://sites.google.com/iiitd.ac.in/sickle/homehttps://sites.google.com/iiitd.ac.in/sickle/home
23. Revolutionize the Oceanic Drone RGB Imagery with Pioneering Sun Glint Detection and Removal Techniques（WACV2024）
24. Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation（WACV2024）
paper:https://openaccess.thecvf.com/content/WACV2024/papers/Nogueira_Prototypical_Contrastive_Network_for_Imbalanced_Aerial_Image_Segmentation_WACV_2024_paper.pdfhttps://openaccess.thecvf.com/content/WACV2024/papers/Nogueira_Prototypical_Contrastive_Network_for_Imbalanced_Aerial_Image_Segmentation_WACV_2024_paper.pdfcode:https://github.com/keillernogueira/proto_ contrastive_net_imbalancedhttps://github.com/keillernogueira/proto_%20contrastive_net_imbalanced
25. C2AIR: Consolidated Compact Aerial Image Haze Removal（WACV2024）
paper:https://openaccess.thecvf.com/content/WACV2024/papers/Kulkarni_C2AIR_Consolidated_Compact_Aerial_Image_Haze_Removal_WACV_2024_paper.pdfhttps://openaccess.thecvf.com/content/WACV2024/papers/Kulkarni_C2AIR_Consolidated_Compact_Aerial_Image_Haze_Removal_WACV_2024_paper.pdfcode:http://https: //github.com/AshutoshKulkarni4998/C2AIRhttp://https//github.com/AshutoshKulkarni4998/C2AIR
26. MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action Recognition（WACV2024）
paper:https://openaccess.thecvf.com/content/WACV2024/papers/Xian_MITFAS_Mutual_Information_Based_Temporal_Feature_Alignment_and_Sampling_for_WACV_2024_paper.pdfhttps://openaccess.thecvf.com/content/WACV2024/papers/Xian_MITFAS_Mutual_Information_Based_Temporal_Feature_Alignment_and_Sampling_for_WACV_2024_paper.pdfcode:GitHub - Ricky-Xian/MITFAS: This is the official implementation of MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action Recognition(https://arxiv.org/abs/2303.02575).This is the official implementation of MITFAS: Mutual Information based Temporal Feature Alignment and Sampling for Aerial Video Action Recognition(https://arxiv.org/abs/2303.02575). - Ricky-Xian/MITFAShttps://github.com/Ricky-Xian/MITFAS
27. Multi-Class Segmentation from Aerial Views using Recursive Noise Diffusion（WACV2024）
paper:https://openaccess.thecvf.com/content/WACV2024/papers/Kolbeinsson_Multi-Class_Segmentation_From_Aerial_Views_Using_Recursive_Noise_Diffusion_WACV_2024_paper.pdfhttps://openaccess.thecvf.com/content/WACV2024/papers/Kolbeinsson_Multi-Class_Segmentation_From_Aerial_Views_Using_Recursive_Noise_Diffusion_WACV_2024_paper.pdfcode:https://github.com/ benediktkol/recursive-noise-diffusionhttps://github.com/%20benediktkol/recursive-noise-diffusion
28. NOMAD: A Natural, Occluded, Multi-scale Aerial Dataset, for Emergency Response Scenarios（WACV2024）
29. CHAI: Craters in Historical Aerial Images（WACV2024）
数据集
Dataset for Object deTection in Aerial images（DOTA数据集）
- DOTA数据集论文介绍：https://arxiv.org/pdf/1711.10398.pdf
- 数据集官网：https://captain-whu.github.io/DOTA/dataset.html
图片尺寸800×800～20000×20000
DOTAV1.0（2018）
类别数目：15
类别名称：plane, ship, storage tank, baseball diamond, tennis court, basketball court, ground track field, harbor, bridge, large vehicle, small vehicle, helicopter, roundabout, soccer ball field , swimming pool
DOTAV1.5（2019）
类别数目：16
类别名称：plane, ship, storage tank, baseball diamond, tennis court, basketball court, ground track field, harbor, bridge, large vehicle, small vehicle, helicopter, roundabout, soccer ball field, swimming pool , container crane
DOTAV2.0（2021）
类别数目：18
类别名称：plane, ship, storage tank, baseball diamond, tennis court, basketball court, ground track field, harbor, bridge, large vehicle, small vehicle, helicopter, roundabout, soccer ball field, swimming pool, container crane, airport , helipad
标注方式：oriented bounding box（定向边界框，即旋转边界框）
标签：x1~y4一个矩形框四个角的坐标，category表示对象类别，difficult表示识别难易程度，0表示简单，1表示困难。
x1, y1, x2, y2, x3, y3, x4, y4, category, difficult
x1, y1, x2, y2, x3, y3, x4, y4, category, difficult
...
DIOR/DIOR-R数据集
- DIOR数据集论文介绍：https://arxiv.org/ftp/arxiv/papers/1909/1909.00133.pdf
- 数据集官网：http://www.escience.cn/people/gongcheng/DIOR.html
- DIOR-R数据集论文介绍：https://arxiv.org/pdf/2110.01931.pdf
- 数据集官网：https://github.com/jbwang1997/AOPG
DIOR数据集（水平边界框）：20个类--飞机、机场、棒球场、篮球场、桥梁、烟囱、水坝、高速公路服务区、高速公路收费站、港口、高尔夫球场、地面田径场、天桥、船舶、体育场、储罐、网球场、火车站、车辆和风磨。由23463张遥感图像和190288个目标实例组成，图像大小为800×800。
DIOR-R数据集（旋转边界框）：在DIOR数据集的基础上，对目标实例重新标注边框，采用旋转框标注，这样避免了水平框的重叠问题。数据集格式需要转换成DOTA格式。
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