992 datasets found

Diffusion models have recently emerged as the state-of-the-art of generative modeling, demonstrating remarkable results in image synthesis and across other modalities.

Diffusion Models are popular generative modeling methods in various vision tasks, attracting significant attention. They can be considered a unique instance of self-supervised...

The dataset used in the paper is the NuScenes dataset, which contains LiDAR point clouds and corresponding semantic annotations.

The dataset used in the paper is the ImageNet and MS COCO benchmarks.

A real dataset of depth images of fabrics, with mechanical ground truth parameters, used to test and evaluate a method for estimating fabric mechanics from depth images.

A synthetic dataset of depth images of fabrics, with mechanical ground truth parameters, used to train and evaluate a method for estimating fabric mechanics from depth images.

The dataset used for training and testing the direct regression model, sparse correspondence model, and dense correspondence model.

The dataset used for learning-based methods for online eye-in-hand camera calibration from a single RGB image.

ScanRefer is a dataset of 51,583 referring descriptions of 11,046 objects from 800 ScanNet scenes.

Training neural networks on image datasets generally require extensive experimentation to find the optimal learning rate regime.

The dataset used in the paper is CIFAR-100 and ImageNet.

A binary imbalanced classification dataset with 32 × 32 color images of 10 classes of natural objects.

The dataset used in this paper for hand-drawn symbol recognition of surgical flowsheet graphs with deep image segmentation.

The FULL1 and FULL2 datasets are subsets of the Oxford RobotCar dataset, with longer route lengths.

The LOOP1 and LOOP2 datasets are subsets of the Oxford RobotCar dataset, with shorter route lengths.

The KITTI360 dataset is used for evaluating the proposed Tuple-Circle loss function for cross-modality feature learning. The dataset consists of image and LiDAR scan pairs.

PhotoBot is a framework for fully automated photo acquisition based on an interplay between high-level human language guidance and a robot photographer.

The dataset used in the paper is the Imagenet dataset, which is a large annotated dataset of images used for image classification tasks.

The Kubric dataset offers training and validation data across various difficulty levels, featuring videos of objects interacting with each other.

The Physion dataset provides training, validation, and testing data for seven scenarios, such as dominoes and support, involving rigid-body objects colliding as well as one...