320 datasets found

The Traffic Signs dataset contains 39252 training images in 43 classes.

The dataset used in this paper is ImageNet-1000 pre-trained CNNs.

Graph Edit Distance as a quadratic assignment problem.

We use the preprocessed binarized MNIST dataset from [49] which has a split of 50k/10k/10k.

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.

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...

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the OpenImages dataset to train their models.

The Moving MNIST dataset consists of videos of MNIST digits.

KITTI 2012 is a real-world dataset in the outdoor scenario, and contains 194 training and 195 testing stereo image pairs with the size of 376 × 1240.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used DeiT and ViT models on ImageNet-1k and CIFAR-100 datasets.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used DeiT and ViT models on ImageNet-1k and CIFAR-100 datasets.

The Pix3D dataset is a dataset of pairs of natural images and CAD models.

Object counting in images

The dataset used in the paper for unsupervised single image intrinsic decomposition.

The NEAT dataset, used for training and evaluation of the Neural Attention Fields (NEAT) model.

The CARLA dataset is a complex urban-like environment with multi-agent dynamics, pedestrians, intersections, cross-traffic, roundabout, and changing weather conditions.