All Projects → yoosan → i3d-tensorflow

yoosan / i3d-tensorflow

Licence: MIT License
Inflated 3D ConvNets for video understanding

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to i3d-tensorflow

Tensornets
High level network definitions with pre-trained weights in TensorFlow
Stars: ✭ 982 (+2034.78%)
Mutual labels:  resnet, inception
Keras Idiomatic Programmer
Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework
Stars: ✭ 720 (+1465.22%)
Mutual labels:  resnet, inception
Tianchi Medical Lungtumordetect
天池医疗AI大赛[第一季]:肺部结节智能诊断 UNet/VGG/Inception/ResNet/DenseNet
Stars: ✭ 314 (+582.61%)
Mutual labels:  resnet, inception
DeepNetModel
记录每一个常用的深度模型结构的特点(图和代码)
Stars: ✭ 25 (-45.65%)
Mutual labels:  resnet, inception
M Pact
A one stop shop for all of your activity recognition needs.
Stars: ✭ 85 (+84.78%)
Mutual labels:  resnet, inception
Pretrained Models.pytorch
Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
Stars: ✭ 8,318 (+17982.61%)
Mutual labels:  resnet, inception
Dogs vs cats
猫狗大战
Stars: ✭ 570 (+1139.13%)
Mutual labels:  resnet, inception
Caffe Model
Caffe models (including classification, detection and segmentation) and deploy files for famouse networks
Stars: ✭ 1,258 (+2634.78%)
Mutual labels:  resnet, inception
mxnet-retrain
Create mxnet finetuner (retrain) for mac/linux ,no need install docker and supports CPU, GPU(eGpu/cudnn).support the inception,resnet ,squeeznet,mobilenet...
Stars: ✭ 32 (-30.43%)
Mutual labels:  resnet, inception
neural-dream
PyTorch implementation of DeepDream algorithm
Stars: ✭ 110 (+139.13%)
Mutual labels:  resnet, inception
general backbone
No description or website provided.
Stars: ✭ 37 (-19.57%)
Mutual labels:  resnet
resnet.torch
an updated version of fb.resnet.torch with many changes.
Stars: ✭ 35 (-23.91%)
Mutual labels:  resnet
RMNet
RM Operation can equivalently convert ResNet to VGG, which is better for pruning; and can help RepVGG perform better when the depth is large.
Stars: ✭ 129 (+180.43%)
Mutual labels:  resnet
Retinal-Disease-Diagnosis-With-Residual-Attention-Networks
Using Residual Attention Networks to diagnose retinal diseases in medical images
Stars: ✭ 14 (-69.57%)
Mutual labels:  resnet
pseudo-3d-pytorch
No description or website provided.
Stars: ✭ 29 (-36.96%)
Mutual labels:  c3d
Gradient-Samples
Samples for TensorFlow binding for .NET by Lost Tech
Stars: ✭ 53 (+15.22%)
Mutual labels:  resnet
CBAM-tensorflow-slim
CBAM implementation on TensorFlow Slim
Stars: ✭ 104 (+126.09%)
Mutual labels:  resnet
CoreML-samples
Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools.
Stars: ✭ 38 (-17.39%)
Mutual labels:  resnet
resnet-ensemble
Ensemble code for Resnet in Tensorflow slim
Stars: ✭ 14 (-69.57%)
Mutual labels:  resnet
IncetOps
基于Inception,一个审计、执行、回滚、统计sql的开源系统
Stars: ✭ 46 (+0%)
Mutual labels:  inception

I3D-TensorFlow

This repo contains the inflated version of the recently popular ConvNets.

Convert weights from the pretrained model

DeepMind have provided the Inception-v1 inflated 3D model, building upon the sonnet. I slightly modified their code and rewrited the i3d model using the protogenetic tensorflow op. The pretrained weights from kinetics-i3d can be easily migrated to the new model. To botain the weights from kinetics-i3d, execute the following instructions.

$ git clone https://github.com/yoosan/i3d-tensorflow
$ cd i3d-tensorflow
$ git clone https://github.com/deepmind/kinetics-i3d
$ python convert_weights.py

Training the I3D model on UCF101

Now I'm preparing the code for training model on the UCF101 dataset. Using the kinetics pretrained weights, we achive a result of 95.2% top-1 accuracy on split 1 of UCF101 with RGB modality.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].