320 datasets found

Deep Neural Networks (DNNs) are universal function approximators providing state-of-the-art solutions on wide range of applications. Common perceptual tasks such as speech...

The Pix3D dataset is a collection of 3D models with RGB images, used for training and testing 3D object recognition and generation tasks.

The dataset used in this paper for convolutional neural networks (CNNs) with approximate multiplication.

Neural Radiance Fields (NeRFs) model a 3D scene as a volumetric function, which can be rendered from arbitrary viewpoints to generate highly-realistic images.

The dataset used in the paper is CIFAR-10, CIFAR-100 and ImageNet-1K.

The dataset used in the paper is the ImageNet-C dataset, which is a dataset of images corrupted with various types of noise and occlusions.

The dataset used in this paper is a MobileNetV2 model, which is a type of deep neural network. The dataset is used to evaluate the performance of the proposed heterogeneous system.

3D Convolutional Neural Networks are sensitive to transformations applied to their input. This is a problem because a voxelized version of a 3D object, and its rotated clone,...

The Street View House Number (SVHN) dataset consists of 32x32 RGB images of house numbers captured from Google Street View.

Real world datasets often contain entries with missing elements e.g. in a medical dataset, a patient is unlikely to have taken all possible diagnostic tests.

The dataset used in the paper is not explicitly described. However, it is mentioned that the authors used a range of datasets, including CIFAR-10, GTSRB, Google Speech Command,...

The DTU MVS Dataset and the Local Light Field Fusion Dataset are used to evaluate the performance of the proposed GARF model.

The dataset for 2D triangle packing, 2D shape arrangement with qualitative constraints, 3D object stacking with stability constraints, and 3D object packing with robots.

The dataset used in this paper is the Meta Research's Segment Anything Model (SAM) dataset, which consists of images.

The ScanNet dataset is a large-scale indoor dataset composed of monocular sequences with ground truth poses and depth images.

Habitat-Matterport 3D (HM3D) dataset includes realistc scans of 1,000 buildings.

Gibson dataset includes realistic scans of 572 full buildings.

The dataset used in the paper is CIFAR-10, STL-10, and ImageNet.

The dataset used in this paper is a ResNet50 model, which is a convolutional neural network. The model is used to evaluate the effects of quantization on the compute...

The dataset used in the paper is CIFAR-10 and ILSVRC-2012.