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Techniques for deep learning with satellite & aerial imagery
🧑🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gan…
用于遥感图像场景分析的中文多模态大模型 | Chinese multimodal large-scale model for remote sensing image scene analysis
[CVMJ2024] Learning Accurate Template Matching with Differentiable Coarse-to-fine Correspondence Refinement
OpenMMLab Self-Supervised Learning Toolbox and Benchmark
PyTorch implementation of SimCLR: supports multi-GPU training and closely reproduces results
SimCLRv2 - Big Self-Supervised Models are Strong Semi-Supervised Learners
PyTorch implementation of SimCLR: A Simple Framework for Contrastive Learning of Visual Representations
A public Dataset for Fine-Grained Ship Classification in Remote sensing images
PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722
YOLOv10: Real-Time End-to-End Object Detection
Official implementation for DMNet: Density map guided object detection in aerial image (CVPR 2020 EarthVision workshop)
Stable Diffusion web UI
Single Image Crowd Counting via MCNN (Unofficial Implementation)
The sample code for a large-scale crowd counting dataset, NWPU-Crowd.
[ICLR 2020] Lite Transformer with Long-Short Range Attention
A2-Nets: Double Attention Networks. NIPS 2018
HCPLab-SYSU / SKT
Forked from chen-judge/SKTSKT distillation (ACM MM 2020)
A dataset built by Central South University for urban scene classification
收录及复现的高光谱遥感图像分类模型
Buildings detection from satellite imagery (8 and 3 bands images) using 2 object detectors : YOLO and Faster RCNN
Demonstration of Using TensorFlow Object Detection API against SpaceNet Data
A sample project demonstrating how to extract building footprints from satellite images using a semantic segmentation model. Data from the SpaceNet Challenge.