68 datasets found

The dataset used in this paper is the 3D-Shapes dataset, a 3D shape classification dataset.

The dataset used in the paper is a MPI3D dataset, which contains 3D images of objects with varying sizes and colors.

Domain generalization for object recognition with multi-task autoencoders.

The THINGS dataset is a large-scale object concept dataset.

A dataset of 3D models, including chairs, tables, and other objects.

The dataset used in this paper for 3D point cloud classification and adversarial example generation.

Zhou et al. (2023) - Sparsefusion

Common Objects in 3D (CO3Dv2)

A neuromorphic vision sensing (NVS) device represents visual information as sequences of asynchronous discrete events (a.k.a., “spikes”) in response to changes in scene...

The ModelNet10 dataset contains 8,000 training and 2,000 test 3D models of objects.

Coil20 is an object dataset consisting of 20 different object categories. 72 images per object are captured at different viewing angles with a total of 1440 images.

iCubWorld Transformations (iCWT): a dataset for object recognition and manipulation

Recognizing person in UAV images faces two main challenges: significant size difference and uncertain rotation variations.

Recognizing person in UAV images faces two main challenges: significant size difference and uncertain rotation variations.

LINEMOD dataset is a widely used instance-level 6D object pose estimation dataset which consists of 13 different objects with significant shape variation.

The dataset used in the paper is a collection of images of objects with varying viewpoints, used for training and testing the proposed RRB framework.

The ModelNet40 dataset is a collection of 3D models, each with multiple views and annotations.

Video object segmentation is challenging due to the factors like rapidly fast motion, cluttered backgrounds, arbitrary object appearance variation and shape deformation.

The Sketchy dataset contains sketches of objects and scenes

Interaction Networks: Using a Reinforcement Learner to train other Machine Learning algorithms