Most recent papers and code on animal detection, remote sensing, and background estimation using aerial imagery.
- Masked Autoencoders Are Scalable Vision Learners [paper] [code]. The original MAE paper by Kaiming He.
- RingMo: A Remote Sensing Foundation Model With Masked Image Modeling [paper] [code]. IEEE Geoscience and Remote Sensing.
- SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery [paper] [code]. Neurips 2022, Stanford.
- Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning [paper]. Arxiv.
- Autoencoder-based background reconstruction and foreground segmentation with background noise estimation [paper]. WACV 2023.
- Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model [paper] [code]. IEEE Geoscience and Remote Sensing.
- Swin MAE: Masked Autoencoders for Small Datasets [paper] [code]. Computers in Biology and Medicine 2023.
- Industrial Image Anomaly Detection Method Based on Improved MAE [paper] ICAC 2023.
- Vision-Language Models in Remote Sensing: Current Progress and Future Trends [paper]. Arxiv 2023.
- RemoteCLIP: A Vision Language Foundation Model for Remote Sensing [paper] [code]. Arxiv 2023.
- Samgeo: A Python package for segmenting geospatial data with the Segment Anything Model (SAM) 🗺️[link]