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ThreshNet: An Efficient DenseNet Using Threshold Mechanism to Reduce Connections
The proposed network architecture uses a threshold mechanism to further optimize the connection method, reducing connections between layers to accelerate inference time. -
Brain-Score
A large-scale benchmark for evaluating the brain-likeness of neural networks. -
JAWS: Just A Wild Shot for Cinematic Transfer in Neural Radiance Fields
The dataset used in the paper for cinematic motion transfer, consisting of NeRF representations of 3D scenes and reference video clips. -
Generative Adversarial Networks
Generative Adversarial Networks (GANs) consist of two networks: a generator G(z) and a discriminator D(x). The discriminator is trying to distinguish real objects from objects... -
Density-Aware NeRF Ensembles (DANE) dataset
This dataset is used for density-aware NeRF ensembles. -
FlipNeRF dataset
This dataset is used for few-shot novel view synthesis. -
MNIST and CIFAR-10 datasets
The MNIST and CIFAR-10 datasets are used to test the theory suggesting the existence of many saddle points in high-dimensional functions. -
Instant Neural Graphics Primitives with a Multiresolution Hash Encoding
The dataset used in the paper is a multiresolution hash encoding for neural graphics primitives. -
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 -
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,... -
N-object dataset testing
An N-object dataset for testing the proposed framework -
Neural 3D Video Synthesis from Multi-View Video
The DyNeRF dataset contains 3D dynamic scenes with moving or deforming objects. -
Streaming Radiance Fields for 3D Video Synthesis
The MeetRoom dataset contains 3D dynamic scenes with moving or deforming objects. -
D-NeRF: Neural Radiance Fields for Dynamic Scenes
The D-NeRF dataset contains 3D dynamic scenes with moving or deforming objects.
