Try out deep learning models online on Google Colab

Related tags

Deep Learningdeep-neural-networksdeep-learningtensorflowjupyter-notebookcnnpytorchjupyter-notebooksgoogle-colabcolab-notebookgoogle-colaboratory
Overview

Try out deep learning models online on Colab with a single click.

TTS

Speech Recognition

Object Detection

Segmentation

Multi Object Tracking

Pose Detection

Scene Text Detection

GAN

Misc

Owner
Erdene-Ochir Tuguldur
Берлиний Техникийн Их Сургууль
Erdene-Ochir Tuguldur
GitHub Repository
Official PyTorch implementation for "Low Precision Decentralized Distributed Training with Heterogenous Data"

Low Precision Decentralized Training with Heterogenous Data Official PyTorch implementation for "Low Precision Decentralized Distributed Training with

Aparna Aketi 0 Nov 23, 2021
Repository providing a wide range of self-supervised pretrained models for computer vision tasks.

Hierarchical Pretraining: Research Repository This is a research repository for reproducing the results from the project "Self-supervised pretraining

Colorado Reed 53 Nov 09, 2022
Repository of our paper 'Refer-it-in-RGBD' in CVPR 2021

Refer-it-in-RGBD This is the repository of our paper 'Refer-it-in-RGBD: A Bottom-up Approach for 3D Visual Grounding in RGBD Images' in CVPR 2021 Pape

Haolin Liu 34 Nov 07, 2022
Methods to get the probability of a changepoint in a time series.

Bayesian Changepoint Detection Methods to get the probability of a changepoint in a time series. Both online and offline methods are available. Read t

Johannes Kulick 554 Dec 30, 2022
Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning, CVPR 2021

Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning By Zhenda Xie*, Yutong Lin*, Zheng Zhang, Yue Ca

Zhenda Xie 293 Dec 20, 2022
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.

Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations

Facebook Research 75 Dec 19, 2022
An easier way to build neural search on the cloud

An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g

Jina AI 17k Jan 02, 2023
MacroTools provides a library of tools for working with Julia code and expressions.

MacroTools.jl MacroTools provides a library of tools for working with Julia code and expressions. This includes a powerful template-matching system an

FluxML 278 Dec 11, 2022
Creating multimodal multitask models

Fusion Brain Challenge The English version of the document can be found here. Обновления 01.11 Мы выкладываем пример данных, аналогичных private test

Sber AI 43 Nov 28, 2022
Lightwood is Legos for Machine Learning.

Lightwood is like Legos for Machine Learning. A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glu

MindsDB Inc 312 Jan 08, 2023
Synthetic Humans for Action Recognition, IJCV 2021

SURREACT: Synthetic Humans for Action Recognition from Unseen Viewpoints Gül Varol, Ivan Laptev and Cordelia Schmid, Andrew Zisserman, Synthetic Human

Gul Varol 59 Dec 14, 2022
The project covers common metrics for super-resolution performance evaluation.

Super-Resolution Performance Evaluation Code The project covers common metrics for super-resolution performance evaluation. Metrics support The script

xmy 10 Aug 03, 2022
Notebooks, slides and dataset of the CorrelAid Machine Learning Winter School

CorrelAid Machine Learning Winter School Welcome to the CorrelAid ML Winter School! Task The problem we want to solve is to classify trees in Roosevel

CorrelAid 12 Nov 23, 2022
Editing a Conditional Radiance Field

Editing Conditional Radiance Fields Project | Paper | Video | Demo Editing Conditional Radiance Fields Steven Liu, Xiuming Zhang, Zhoutong Zhang, Rich

Steven Liu 216 Dec 30, 2022
Machine Translation Implement By Bi-GRU And Transformer

Seq2Seq Translation Implement By Bidirectional GRU And Transformer In Pytorch Before You Run The Code You should download the data through the link be

He Wang 2 Oct 27, 2021
Official implementation of "Open-set Label Noise Can Improve Robustness Against Inherent Label Noise" (NeurIPS 2021)

Open-set Label Noise Can Improve Robustness Against Inherent Label Noise NeurIPS 2021: This repository is the official implementation of ODNL. Require

Hongxin Wei 12 Dec 07, 2022
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Intelligent Robotics and Machine Vision Lab 4 Jul 19, 2022
A PyTorch implementation of SIN: Superpixel Interpolation Network

SIN: Superpixel Interpolation Network This is is a PyTorch implementation of the superpixel segmentation network introduced in our PRICAI-2021 paper:

6 Sep 28, 2022
Code for Blind Image Decomposition (BID) and Blind Image Decomposition network (BIDeN).

arXiv, porject page, paper Blind Image Decomposition (BID) Blind Image Decomposition is a novel task. The task requires separating a superimposed imag

64 Dec 20, 2022
Source code for models described in the paper "AudioCLIP: Extending CLIP to Image, Text and Audio" (https://arxiv.org/abs/2106.13043)

AudioCLIP Extending CLIP to Image, Text and Audio This repository contains implementation of the models described in the paper arXiv:2106.13043. This

458 Jan 02, 2023