68 datasets found

The dataset used for 6D object pose estimation, consisting of images of 16 objects with varying levels of occlusion.

The Objaverse dataset contains around 800k 3D objects. After adopting simple filter leveraging CLIP [27] to remove the objects whose rendered images are not relevant to its...

The dataset used in the paper is a real-world 3D point cloud dataset, which is used for 3D shape classification, part segmentation, and shape retrieval tasks.

CORe50 is a video benchmark for continual learning, consisting of 164,866 128x128 images of 50 domestic objects belonging to 10 categories.

The dataset used for training and validation of the proposed approach to combine semantic segmentation and dense outlier detection.

The dataset used in this paper for object recognition on CIFAR-100, MNIST, and ImageNet, and scene recognition on MIT67, SUN397, and Places205.

Google Scanned Objects is a real-scanned 3D object dataset and we use all its 1030 samples for evaluation unlike existing works [29, 31] that only use 30 of them.

Point cloud registration is a crucial problem in computer vision and robotics. Existing methods either rely on matching local geometric features, which are sensitive to the pose...