This is implementation of AlexNet(2012) with 3D Convolution on TensorFlow (AlexNet 3D).

Last update: Jan 16, 2022

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Deep Learning AlexNet3D

Overview

AlexNet_3dConv

TensorFlow implementation of AlexNet(2012) by Alex Krizhevsky, with 3D convolutiional layers.

3D AlexNet

Network with a standart AlexNet architecture, but it has 3D instead 2D filters on each Conv and Pool layers.

Standart AlexNet

To fit this model into memory, model training proccess can be refactored with @OpenAI's `Gradient Checkpointing` algorithm https://github.com/openai/gradient-checkpointing

Note: This model needs a lot of GPU memory. Training session will not starts on 1 GPU without additional data separation or code's parallelization (or https://github.com/openai/gradient-checkpointing for example).
Note2: This model doesn't pretend to be the SilverBullet in 3D image recognition (like AlexNet was in 2D). It's just an example of 3D convolutional model in TensorFlow.

Owner

Denis Timonin

AI Solutions Architect at NVIDIA

GitHub Repository

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This is implementation of AlexNet(2012) with 3D Convolution on TensorFlow (AlexNet 3D).

Related tags

Overview

AlexNet_3dConv

3D AlexNet

Standart AlexNet

To fit this model into memory, model training proccess can be refactored with @OpenAI's `Gradient Checkpointing` algorithm https://github.com/openai/gradient-checkpointing

Owner

Denis Timonin

the code used for the preprint Embedding-based Instance Segmentation of Microscopy Images.

Iowa Project - My second project done at General Assembly, focused on feature engineering and understanding Linear Regression as a concept

MBPO (paper: When to trust your model: Model-based policy optimization) in offline RL settings

Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation

Research code for CVPR 2021 paper "End-to-End Human Pose and Mesh Reconstruction with Transformers"

Implementation of FSGNN

Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentation"

Official code for "Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021".

Confident Semantic Ranking Loss for Part Parsing

Clustering with variational Bayes and population Monte Carlo

Motion Reconstruction Code and Data for Skills from Videos (SFV)

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)

Code for the CVPR2022 paper "Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity"

Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation

Implementation of PyTorch-based multi-task pre-trained models

Here is the diagnostic tool for BMVC 2021 paper Diagnosing Errors in Video Relation Detectors.

Group Activity Recognition with Clustered Spatial Temporal Transformer

Build a medical knowledge graph based on Unified Language Medical System (UMLS)

Computer Vision application in the web

This is implementation of AlexNet(2012) with 3D Convolution on TensorFlow (AlexNet 3D).

Related tags

Overview

AlexNet_3dConv

3D AlexNet

Standart AlexNet

To fit this model into memory, model training proccess can be refactored with @OpenAI's Gradient Checkpointing algorithm https://github.com/openai/gradient-checkpointing

Owner

Denis Timonin

the code used for the preprint Embedding-based Instance Segmentation of Microscopy Images.

Iowa Project - My second project done at General Assembly, focused on feature engineering and understanding Linear Regression as a concept

MBPO (paper: When to trust your model: Model-based policy optimization) in offline RL settings

Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Implementation

Research code for CVPR 2021 paper "End-to-End Human Pose and Mesh Reconstruction with Transformers"

Implementation of FSGNN

Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentation"

Official code for "Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer. ICCV2021".

Confident Semantic Ranking Loss for Part Parsing

Clustering with variational Bayes and population Monte Carlo

Motion Reconstruction Code and Data for Skills from Videos (SFV)

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

Official PyTorch implementation of "Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets" (ICLR 2021)

Code for the CVPR2022 paper "Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity"

Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation

Implementation of PyTorch-based multi-task pre-trained models

Here is the diagnostic tool for BMVC 2021 paper Diagnosing Errors in Video Relation Detectors.

Group Activity Recognition with Clustered Spatial Temporal Transformer

Build a medical knowledge graph based on Unified Language Medical System (UMLS)

Computer Vision application in the web

To fit this model into memory, model training proccess can be refactored with @OpenAI's `Gradient Checkpointing` algorithm https://github.com/openai/gradient-checkpointing