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Found 6 papers, 3 papers with code
RS-MoE: Mixture of Experts for Remote Sensing Image Captioning and Visual Question Answering
We fine-tuned our model on the RSICap dataset using our proposed training strategy.
LG-VQ: Language-Guided Codebook Learning
Vector quantization (VQ) is a key technique in high-resolution and high-fidelity image synthesis, which aims to learn a codebook to encode an image with a sequence of discrete codes and then generate an image in an auto-regression manner.
MCSDNet: Mesoscale Convective System Detection Network via Multi-scale Spatiotemporal Information
Different from the previous models, MCSDNet targets on multi-frames detection and leverages multi-scale spatiotemporal information for the detection of MCS regions in remote sensing imagery(RSI).
DiffCast: A Unified Framework via Residual Diffusion for Precipitation Nowcasting
A unified and flexible framework that can equip any type of spatio-temporal models is proposed based on residual diffusion, which effectively tackles the shortcomings of previous methods.
MetaDiff: Meta-Learning with Conditional Diffusion for Few-Shot Learning
Its key idea is learning a deep model in a bi-level optimization manner, where the outer-loop process learns a shared gradient descent algorithm (i. e., its hyperparameters), while the inner-loop process leverage it to optimize a task-specific model by using only few labeled data.
RAP-Net: Region Attention Predictive Network for Precipitation Nowcasting
Natural disasters caused by heavy rainfall often cost huge loss of life and property.
