[CVPR2024] 🥥COCONut: Crafting the Future of Segmentation Datasets with Exquisite Annotations in the Era of ✨Big Data✨
Xueqing Deng, Qihang Yu, Peng Wang, Xiaohui Shen, Liang-Chieh Chen
🔥 1st large-scale human verified dataset for segmentation, more info can be found at our website.
🔥 COCONut is now available at Kaggle, welcome to download!
- 4/25: Tutorial on visualizing COCONut panoptic masks using detectron2. Turn the black mask image into overlayed colorful mask.
- 4/24: Collected FAQs are out, please check them before you leave any issue.
- 4/22: Tutorial on instance segmentation is out! More are coming!
- 4/19: Tutorial on panoptic segmentation is out!
- 4/16: COCONut is available at Kaggle! No need to merge COCONut-B from COCONut-S, update a version of ready-to-use.
- 4/15: COCONut is higlighted by AK's daily paper!
- 4/15: Huggingface download links are temporarily closed.
- Huggingface dataset preview
- Convert the annotation to semantic segmentation and object detection.
- Release COCONut-L and COCONut-val by the end of April
| Splits | #images | #masks | images | annotations |
|---|---|---|---|---|
| COCONut-S | 118K | 1.54M | download | Kaggle |
| COCONut-B | 242K | 2.78M | download | Kaggle |
| COCONut-L | 358K | 4.75M | coming | coming |
| relabeled-COCO-val | 5K | 67K | download | Kaggle |
| COCONut-val | 25K | 437K | coming | coming |
We only provide the annotation, for those who are interested to use our annotation will need to download the images from the links: COCONut-S images, COCONut-B images and relabeled COCO-val images.
We summarize the common issues in FAQ.md, please check this out before you create any new issues.
If you find our dataset useful, please cite:
@inproceedings{coconut2024cvpr,
author = {Xueqing Deng, Qihang Yu, Peng Wang, Xiaohui Shen, Liang-Chieh Chen},
title = {COCONut: Modernizing COCO Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {2024},
We follow the same license as COCO dataset for images. For COCONut's annotations, non-commercial use are allowed.