70 datasets found

The RLBench dataset is used for robot learning benchmark and learning environment.

DocBank consists of 500K document layouts by weak supervision of articles available on the arXiv.com.

A new benchmark named D4LA, which is the most diverse and detailed manually-labeled dataset for document layout analysis.

A benchmark dataset for face detection, with 32,203 images and 393,703 faces.

The MoleculeNet dataset is a collection of molecular property prediction tasks. It contains 17 datasets, each with a different type of molecular graph.

CVSS-C benchmark for speech-to-speech translation

CLIMABENCH is a benchmark of climate-related text classification tasks. It collates five existing climate change-related text datasets, including CLIMATEXT, CLIMATESTANCE,...

The UKB object recognition benchmark.

The Holidays dataset is used for testing the performance of the HAE on visual feature translation.

The Urban100 dataset is a benchmark for image denoising, containing 100 images with varying levels of noise.

The dataset used in the paper is RLBench, a standard benchmark for vision-based robotics which has been shown to serve as a proxy for real-robot experiments.

The dataset used in this paper is the BSDS500 dataset, which contains 200 natural images with over 1000 ground truth labellings.

A broad benchmark for applying machine learning models to solid-state materials.

speechocean762: An open-source non-native English speech corpus for pronunciation assessment.

The dataset used in the paper is a code generation benchmark, consisting of 164 function declarations alongside their documentation, 500 test examples, each one is an...

VLCS dataset is a benchmark for image classification, containing images from four different datasets (domains): VOC2007, LabelMe, Caltech, and SUN09.

The RL Unplugged dataset, a benchmark for offline reinforcement learning, consisting of 20 tasks with varying difficulty levels.

The YCB object and model set is a benchmark for manipulation research, consisting of 15 object categories and 3D models.

A benchmark dataset for cell nuclei segmentation, featuring approximately 700 segmented cell images.

The proposed method, dubbed Dynamic Hyperpixel Flow, learns to compose hypercolumn features on the fly by selecting a small number of relevant layers from a deep convolutional...