RSIEval
数据集名称: RSIEval 任务: 遥感图像字幕、问答 发布时间: 2023 模态: 图像、文本 数量: 100个人工注释的标题和936个视觉问答对,包含丰富的信息和开放式的问题和答案。 代码源链接: https://github.com/Lavender105/RSGPT 论文源链接: https://arxiv.org/abs/2307.15266
数据集名称: RSIEval 任务: 遥感图像字幕、问答 发布时间: 2023 模态: 图像、文本 数量: 100个人工注释的标题和936个视觉问答对,包含丰富的信息和开放式的问题和答案。 代码源链接: https://github.com/Lavender105/RSGPT 论文源链接: https://arxiv.org/abs/2307.15266
论文名称: Change-Aware Sampling and Contrastive Learning for Satellite Images Link: https://openaccess.thecvf.com/content/CVPR2023/html/Mall_Change-Aware_Sampling_and_Contrastive_Learning_for_Sate...
论文名称: CMID: A Unified Self-Supervised Learning Framework for Remote Sensing Image Understanding Link: https://arxiv.org/abs/2304.09670 Published in: TGRS 2023 Type: Pretrain Code/Project...
论文名称: USat: A Unified Self-Supervised Encoder for Multi-Sensor Satellite Imagery Link: https://arxiv.org/abs/2312.02199 Published in: Arxiv 2023 Type: Pretrain Code/Project: https://gith...
论文名称: TOV: The Original Vision Model for Optical Remote Sensing Image Understanding via Self-Supervised Learning Link: https://arxiv.org/abs/2204.04716 Published in: IEEE Journal of Selected...
论文名称: Foundation Models for Generalist Geospatial Artificial Intelligence Link: https://arxiv.org/abs/2310.18660 Published in: Arxiv 2023 Type: Pretrain Code/Project: https://huggingface...
论文名称: Towards Geospatial Foundation Models via Continual Pretraining Link: https://arxiv.org/abs/2302.04476 Published in: ICCV 2023 Type: Pretrain Code/Project: https://github.com/mmendi...
论文名称: A billion-scale foundation model for remote sensing images Link: https://arxiv.org/abs/2304.05215 Published in: Arxiv 2023 Type: Pretrain Code/Project: — Short Summary: 研究参数量对预训练...
论文名称: RSGPT: A Remote Sensing Vision Language Model and Benchmark 模型架构: MLLM Visual Encoder: Transformer Text Encoder: Transformer Model Details: Vision Encoder:EVAText Encoder:Vicuna ...
论文名称: A Self-Supervised Cross-Modal Remote Sensing Foundation Model with Multi-Domain Representation and Cross-Domain Fusion Link: https://ieeexplore.ieee.org/abstract/document/10282433 Publ...