This repo contains research materials released by members of the Google Brain team in Tokyo.

Related tags

Deep Learningbrain-tokyo-workshop
Overview

Brain Tokyo Workshop 🧠 🗼

This repo contains research materials released by members of the Google Brain team in Tokyo.

Past Projects

Weight Agnostic Neural Networks

Code Release

Link to Article (pdf version)

Learning to Predict Without Looking Ahead: World Models Without Forward Prediction

Code Release

Link to Article (pdf version)

Neuroevolution of Self-Interpretable Agents

Code Release (Code for CarRacing Variants)

Extensions to CarRacing-v0 environment released to facilitate future research.

Link to Article (pdf version)

Modern Evolution Strategies for Creativity: Fitting Concrete Images and Abstract Concepts

Code Release

Disclaimer

This is not an official Google product.

Owner
Google
Google ❤️ Open Source
Google
GitHub Repository
3D-Reconstruction 基于深度学习方法的单目多视图三维重建

基于深度学习方法的单目多视图三维重建 Part I 三维重建 代码：Part1 技术文档：[Markdown] [PDF] 原始图像：Original Images 点云结果：Point Cloud Results-1

HMT_Curo 19 Dec 26, 2022
Bayesian dessert for Lasagne

Gelato Bayesian dessert for Lasagne Recent results in Bayesian statistics for constructing robust neural networks have proved that it is one of the be

Maxim Kochurov 84 May 11, 2020
A novel benchmark dataset for Monocular Layout prediction

AutoLay AutoLay: Benchmarking Monocular Layout Estimation Kaustubh Mani, N. Sai Shankar, J. Krishna Murthy, and K. Madhava Krishna Abstract In this pa

Kaustubh Mani 39 Apr 26, 2022
Yolact-keras实例分割模型在keras当中的实现

Yolact-keras实例分割模型在keras当中的实现 目录 性能情况 Performance 所需环境 Environment 文件下载 Download 训练步骤 How2train 预测步骤 How2predict 评估步骤 How2eval 参考资料 Reference 性能情况 训练数

Bubbliiiing 11 Dec 26, 2022
IAUnet: Global Context-Aware Feature Learning for Person Re-Identification

IAUnet This repository contains the code for the paper: IAUnet: Global Context-Aware Feature Learning for Person Re-Identification Ruibing Hou, Bingpe

30 Jul 14, 2022
Tools for investing in Python

InvestOps Original repository on GitHub Original author is Magnus Erik Hvass Pedersen Introduction This is a Python package with simple and effective

24 Nov 26, 2022
Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression

Regression Transformer Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression . Development se

International Business Machines 27 Jan 05, 2023
Towards Implicit Text-Guided 3D Shape Generation (CVPR2022)

Towards Implicit Text-Guided 3D Shape Generation Towards Implicit Text-Guided 3D Shape Generation (CVPR2022) Code for the paper [Towards Implicit Text

55 Dec 16, 2022
Unoffical reMarkable AddOn for Firefox.

reMarkable for Firefox (Download) This repo converts the offical reMarkable Chrome Extension into a Firefox AddOn published here under the name "Unoff

Jelle Schutter 45 Nov 28, 2022
利用yolov5和TensorRT从0到1实现目标检测的模型训练到模型部署全过程

写在前面 利用TensorRT加速推理速度是以时间换取精度的做法，意味着在推理速度上升的同时将会有精度的下降，不过不用太担心，精度下降微乎其微。此外，要有NVIDIA显卡，经测试，CUDA10.2可以支持20系列显卡及以下，30系列显卡需要CUDA11.x的支持，并且目前有bug。 默认你已经完成了

Helium 6 Jul 28, 2022
PyTorch implementations of algorithms for density estimation

pytorch-flows A PyTorch implementations of Masked Autoregressive Flow and some other invertible transformations from Glow: Generative Flow with Invert

Ilya Kostrikov 546 Dec 05, 2022
Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.

Demonstration of OpenVINO techniques - Model-division and a simplest-way to support custom layers Description: Model Optimizer in Intel(r) OpenVINO(tm

Yasunori Shimura 12 Nov 09, 2022
[ICCV 2021] FaPN: Feature-aligned Pyramid Network for Dense Image Prediction

FaPN: Feature-aligned Pyramid Network for Dense Image Prediction [arXiv] [Project Page] @inproceedings{ huang2021fapn, title={{FaPN}: Feature-alig

Shihua Huang 23 Jul 22, 2022
Official pytorch implementation of paper "Image-to-image Translation via Hierarchical Style Disentanglement".

HiSD: Image-to-image Translation via Hierarchical Style Disentanglement Official pytorch implementation of paper "Image-to-image Translation

364 Dec 14, 2022
Generative Exploration and Exploitation - This is an improved version of GENE.

GENE This is an improved version of GENE. In the original version, the states are generated from the decoder of VAE. We have to check whether the gere

33 Mar 23, 2022
Project repo for the paper SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition

SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition (BMVC 2021) Project repo for the paper SILT: Self-supervised Lighting Trans

6 Dec 04, 2022
Kaggle: Cell Instance Segmentation

Kaggle: Cell Instance Segmentation The goal of this challenge is to detect cells in microscope images. with simple view on how many cels have been ann

Jirka Borovec 9 Aug 12, 2022
Deep Video Matting via Spatio-Temporal Alignment and Aggregation [CVPR2021]

Deep Video Matting via Spatio-Temporal Alignment and Aggregation [CVPR2021] Paper: https://arxiv.org/abs/2104.11208 Introduction Despite the significa

76 Dec 07, 2022
Compute descriptors for 3D point cloud registration using a multi scale sparse voxel architecture

MS-SVConv : 3D Point Cloud Registration with Multi-Scale Architecture and Self-supervised Fine-tuning Compute features for 3D point cloud registration

42 Jul 25, 2022
This code is 3d-CNN model that can predict environmental value

Predict-environmental-value-3dCNN This code is 3d-CNN model that can predict environmental value. Firstly, I built a model that can create a lot of bu

1 Jan 06, 2022