COCONut Dataset
COCONut Dataset
Datasets
COCONut Dataset
File
COCONut
Use Case
COCONut
Description
Discover the COCONut Dataset with 383,000 high-quality images and 5.18 million verified panoptic segmentation masks.
Description:
Introducing COCONut, a cutting-edge segmentation dataset that includes around 383,000 images and 5.18 million carefully verified panoptic segmentation masks. Additionally, the dataset features COCONut-val, a new validation set that serves as a challenging testbed for researchers. As a result, COCONut-val aims to push the limits of existing segmentation models. Therefore, it provides a rigorous evaluation platform to benchmark performance and encourage innovation.
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The dataset supports a broad range of tasks, including:
- Panoptic Segmentation
- Instance Segmentation
- Semantic Segmentation
- Object Detection
- Pretraining for Open-Vocabulary Segmentation
- Mask-Conditional Image Synthesis
As we advance into the Era of Big Data, the vast scale and versatility of datasets pave the way for the development of even more innovative tasks. Therefore, we invite the research community to explore its potential and contribute to groundbreaking advancements in the field.
Key Features:
- Extensive Image Collection: Approximately 383,000 high-quality images.
- Verified Annotations: 5.18 million meticulously verified panoptic segmentation masks.
- Versatile Applications: Suitable for a wide array of segmentation and detection tasks.
- Innovative Validation Set: COCONut-val provides a robust testbed for benchmarking.
Discover our dataset and open up new opportunities in segmentation and object detection research. Furthermore, join us in expanding the limits of what’s achievable with our detailed and adaptable data resources.
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