A dataset converted from NYUDv2 into COCO-style instance segmentation format
For detailed statistics about our dataset, please refer to the following paper:
IAM: Enhancing RGB-D Instance Segmentation with New Benchmarks
Train : 795 images
Val : 654 images
Classes : 9
Size : 640 × 480
Sensor : Kinect V1
NYUDv2 : https://huggingface.co/datasets/kasurashan/RGBD-Instance-Segmentation
NYUDv2/
└── train/
└── color/
└── val/
└── color/
└── annotations/
└── instances_train.json
└── instances_val.json
└── depth/
└── hha/
annotation{
"id": int,
"image_id": int,
"category_id": int,
"segmentation": [polygon],
"area": float,
"bbox": [x,y,width,height],
"iscrowd": 0 or 1,
}
categories[{
"id": int,
"name": str,
"supercategory": str,
}]