Update README.md

README.md

@@ -1,3 +1,63 @@
----
-license: mit
----
+---
+license: mit
+task_categories:
+- visual-question-answering
+language:
+- en
+size_categories:
+- 10K<n<100K
+---
+This is a multimodal cross-scenario dataset for continual learning with MLLMs. We provide a simple script to split the dataset in multiple ways.
+
+The dataset format has been adjusted for Qwen. We have retained the original coordinates of the bounding box. You need to adjust the coordinates according to Qwen format.
+
+Detailed information can refer to http://arxiv.org/abs/2511.18507
+
+If you use this datasets, please cite:
+
+@misc{jiang2025multimodalcontinuallearningmllms,
+  title={Multimodal Continual Learning with MLLMs from Multi-scenario Perspectives}, 
+  author={Kai Jiang and Siqi Huang and Xiangyu Chen and Jiawei Shao and Hongyuan Zhang and Xuelong Li},
+  year={2025},
+  eprint={2511.18507},
+  archivePrefix={arXiv},
+  primaryClass={cs.CV},
+  url={https://arxiv.org/abs/2511.18507}, 
+}
+
+Source data is from 4 public datasets:
+
+@article{2022FAIR1M,
+title={FAIR1M: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery},
+author={ Sun, Xian and Wang, Peijin and Yan, Zhiyuan and Xu, Feng and Wang, Ruiping and Diao, Wenhui and Chen, Jin and Li, Jihao and Feng, Yingchao and Xu, Tao },
+journal={ISPRS Journal of Photogrammetry and Remote Sensing},
+volume={184},
+year={2022},
+}
+
+@article{RUOD23,
+    title={Rethinking general underwater object detection: Datasets, challenges, and solutions},
+    author={Chenping, Fu and Risheng, Liu and Xin, Fan and Puyang, Chen and Hao, Fu and Wanqi, Yuan and Ming, Zhu and Zhongxuan, Luo},
+    journal={Neurocomputing},
+    year={2023}
+}
+
+@article{zhu2021detection,
+  title={Detection and tracking meet drones challenge},
+  author={Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin},
+  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
+  volume={44},
+  number={11},
+  pages={7380--7399},
+  year={2021},
+  publisher={IEEE}
+}
+
+@INPROCEEDINGS{Damen2018EPICKITCHENS,
+   title={Scaling Egocentric Vision: The EPIC-KITCHENS Dataset},
+   author={Damen, Dima and Doughty, Hazel and Farinella, Giovanni Maria  and Fidler, Sanja and 
+           Furnari, Antonino and Kazakos, Evangelos and Moltisanti, Davide and Munro, Jonathan 
+           and Perrett, Toby and Price, Will and Wray, Michael},
+   booktitle={European Conference on Computer Vision (ECCV)},
+   year={2018}
+}