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Convolutional Neural Networks with Approximate Multiplication
The dataset used in this paper for convolutional neural networks (CNNs) with approximate multiplication. -
Tanks and Temples
Neural Radiance Fields (NeRFs) model a 3D scene as a volumetric function, which can be rendered from arbitrary viewpoints to generate highly-realistic images. -
CIFAR-10, CIFAR-100 and ImageNet-1K
The dataset used in the paper is CIFAR-10, CIFAR-100 and ImageNet-1K. -
MomentsNeRF: Leveraging Orthogonal Moments for Few-Shot Neural Rendering
A novel framework for one- and few-shot neural rendering that predicts a neural representation of a 3D scene using Orthogonal Moments. -
MobileNetV2
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. -
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis
NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis -
ModelNet10
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,... -
ORB-SLAM3-Enhanced Autonomous Toy Drones: Pioneering Indoor Exploration
The dataset used in the paper is a set of point clouds generated by ORB-SLAM3, a state-of-the-art vision feature-based SLAM system. -
Synthetic Dataset
The dataset used in this work is a custom synthetic dataset generated using the liquid-dsp library, containing 600000 examples of each of 13.8 million examples, with SNRs... -
Street View House Number (SVHN) dataset
The Street View House Number (SVHN) dataset consists of 32x32 RGB images of house numbers captured from Google Street View. -
VAEs in the Presence of Missing Data
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. -
DEMYSTIFYING CLIP DATA
Contrastive Language-Image Pre-training (CLIP) is an approach that has advanced research and applications in computer vision, fueling modern recognition systems and generative... -
RealBlur Test Dataset
The RealBlur test dataset for image deblurring. -
HIDE Test Dataset
The HIDE test dataset for image deblurring. -
GoPro Test Dataset
The GoPro test dataset for image deblurring. -
Arbitrary Bit-Width Network: A Joint Layer-Wise Quantization and Adaptive Inf...
Arbitrary bit-width network: A joint layer-wise quantization and adaptive inference approach. -
Mixed-precision Neural Network Quantization via Learned Layer-wise Importance
Mixed-precision neural network quantization via learned layer-wise importance. -
LUT-NN: Empower Efficient Neural Network Inference with Centroid Learning and...
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,... -
ObjectCompose
ObjectCompose: Evaluating Resilience of Vision-Based Models on Object-to-Background Compositional Changes -
MNIST Database
The MNIST database of handwritten digits is a popular benchmark data set for classification algorithms.
