EssentialMC2 Video Understanding

Overview

EssentialMC2

Introduction

EssentialMC2 is a complete system to solve video understanding tasks including MHRL(representation learning), MECR2( relation reasoning) and MOSL3(openset life-long learning) powered by DAMO Academy MinD(Machine IntelligenNce of Damo) Lab.

Features

  • Simple and easy to use
  • High efficiency
  • Include SOTA papers presented by DAMO Academy
  • Include various pretrained models

Installation

Install by pip

Run pip install essmc2.

Install from source

Requirements
  • Python 3.6+
  • PytTorch 1.5+

Run python setup.py install. For each specific task, please refer to task specific README.

Model Zoo

Will be released soon!

SOTA Tasks

Task Paper
ICCV2021-NGC link
CVPR2021-MoSI link

License

EssentialMC2 is released under MIT license.

MIT License

Copyright (c) 2021 Alibaba

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Acknowledgement

EssentialMC2 is an open source project that is contributed by researchers from DAMO Academy. We appreciate users who give valuable feedbacks.

Owner
Alibaba
Alibaba Open Source
Alibaba
Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering (NAACL 2021)

Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering Abstract In open-domain question answering (QA), retrieve-and-read mec

Clova AI Research 34 Apr 13, 2022
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

Zhiqiang Shen 52 Dec 24, 2022
Restricted Boltzmann Machines in Python.

How to Use First, initialize an RBM with the desired number of visible and hidden units. rbm = RBM(num_visible = 6, num_hidden = 2) Next, train the m

Edwin Chen 928 Dec 30, 2022
PyTorch implementation of Algorithm 1 of "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"

Code for On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models This repository will reproduce the main results from our pape

Mitch Hill 32 Nov 25, 2022
PyTorch code for the NAACL 2021 paper "Improving Generation and Evaluation of Visual Stories via Semantic Consistency"

Improving Generation and Evaluation of Visual Stories via Semantic Consistency PyTorch code for the NAACL 2021 paper "Improving Generation and Evaluat

Adyasha Maharana 28 Dec 08, 2022
A python library for self-supervised learning on images.

Lightly is a computer vision framework for self-supervised learning. We, at Lightly, are passionate engineers who want to make deep learning more effi

Lightly 2k Jan 08, 2023
Pytorch Implementation of the paper "Cross-domain Correspondence Learning for Exemplar-based Image Translation"

CoCosNet Pytorch Implementation of the paper "Cross-domain Correspondence Learning for Exemplar-based Image Translation" (CVPR 2020 oral). Update: 202

Lingbo Yang 38 Sep 22, 2021
A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.

Reinforcement-Learning-Notebooks A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented

Pulkit Khandelwal 1k Dec 28, 2022
A framework for Quantification written in Python

QuaPy QuaPy is an open source framework for quantification (a.k.a. supervised prevalence estimation, or learning to quantify) written in Python. QuaPy

41 Dec 14, 2022
UNet model with VGG11 encoder pre-trained on Kaggle Carvana dataset

TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation By Vladimir Iglovikov and Alexey Shvets Introduction TernausNet is

Vladimir Iglovikov 1k Dec 28, 2022
This project intends to use SVM supervised learning to determine whether or not an individual is diabetic given certain attributes.

Diabetes Prediction Using SVM I explore a diabetes prediction algorithm using a Diabetes dataset. Using a Support Vector Machine for my prediction alg

Jeff Shen 1 Jan 14, 2022
A Multi-modal Perception Tracker (MPT) for speaker tracking using both audio and visual modalities

MPT A Multi-modal Perception Tracker (MPT) for speaker tracking using both audio and visual modalities. Implementation for our AAAI 2022 paper: Multi-

yidiLi 4 May 08, 2022
A generator of point clouds dataset for PyPipes.

CloudPipesGenerator Documentation | Colab Notebooks | Video Tutorials | Master Degree website A generator of point clouds dataset for PyPipes. TODO Us

1 Jan 13, 2022
Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance

Semi-supervised Deep Kernel Learning This is the code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data

58 Oct 26, 2022
Rethinking Portrait Matting with Privacy Preserving

Rethinking Portrait Matting with Privacy Preserving This is the official repository of the paper Rethinking Portrait Matting with Privacy Preserving.

184 Jan 03, 2023
Codes for the ICCV'21 paper "FREE: Feature Refinement for Generalized Zero-Shot Learning"

FREE This repository contains the reference code for the paper "FREE: Feature Refinement for Generalized Zero-Shot Learning". [arXiv][Paper] 1. Prepar

Shiming Chen 28 Jul 29, 2022
Pytorch implementation of forward and inverse Haar Wavelets 2D

Pytorch implementation of forward and inverse Haar Wavelets 2D

Sergei Belousov 9 Oct 30, 2022
Efficient Householder transformation in PyTorch

Efficient Householder Transformation in PyTorch This repository implements the Householder transformation algorithm for calculating orthogonal matrice

Anton Obukhov 49 Nov 20, 2022
[CVPR 2019 Oral] Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation

SelectionGAN for Guided Image-to-Image Translation CVPR Paper | Extended Paper | Guided-I2I-Translation-Papers Citation If you use this code for your

Hao Tang 424 Dec 02, 2022
Official implementation of "DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation"

DSP Official implementation of "DSP: Dual Soft-Paste for Unsupervised Domain Adaptive Semantic Segmentation". Accepted by ACM Multimedia 2021. Authors

20 Oct 24, 2022