The code for MM2021 paper "Multi-Level Counterfactual Contrast for Visual Commonsense Reasoning"

Related tags

Deep LearningMCC
Overview

The Code for MM2021 paper "Multi-Level Counterfactual Contrast for Visual Commonsense Reasoning"

Setting up and using the repo

  1. Get the dataset. Follow the steps in data/README.md. This includes the steps to get the pretrained BERT embeddings and visual representations.

  2. Install cuda 11.0 if it's not available already.

  3. Install anaconda if it's not available already, and create a new environment. You need to install a few things, namely, pytorch 1.7.1, torchvision, and allennlp.

wget https://repo.anaconda.com/archive/Anaconda3-5.2.0-Linux-x86_64.sh
conda update -n base -c defaults conda
conda create --name MCC python=3.6
source activate MCC

conda install numpy pyyaml setuptools cmake cffi tqdm pyyaml scipy ipython mkl mkl-include cython typing h5py pandas nltk spacy numpydoc scikit-learn jpeg

conda install pytorch==1.7.1 torchvision==0.8.2 cudatoolkit=11.0 -c pytorch

pip install -r allennlp-requirements.txt
pip install --no-deps allennlp==0.8.0
python -m spacy download en_core_web_sm


# this one is optional but it should help make things faster
pip uninstall pillow && CC="cc -mavx2" pip install -U --force-reinstall pillow-simd
  1. That's it! Now to set up the environment, run source activate MCC.

Train/Evaluate models

Please refer to models/README.md.

Acknowledgement

  • We refer to the repo r2c and tab-vcr for preprocessing codes.

Cite

@inproceedings{zhang2021multi,
  title={Multi-Level Counterfactual Contrast for Visual Commonsense Reasoning},
  author={Zhang, Xi and Zhang, Feifei and Xu, Changsheng},
  booktitle={Proceedings of the 29th ACM International Conference on Multimedia},
  pages={1793--1802},
  year={2021}
}
A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal

A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases,

Chris Hughes 110 Dec 23, 2022
An Artificial Intelligence trying to drive a car by itself on a user created map

An Artificial Intelligence trying to drive a car by itself on a user created map

Akhil Sahukaru 17 Jan 13, 2022
This repo is developed for Strong Baseline For Vehicle Re-Identification in Track 2 Ai-City-2021 Challenges

A STRONG BASELINE FOR VEHICLE RE-IDENTIFICATION This paper is accepted to the IEEE Conference on Computer Vision and Pattern Recognition Workshop(CVPR

Cybercore Co. Ltd 78 Dec 29, 2022
This repository is for DSA and CP scripts for reference.

dsa-script-collections This Repo is the collection of DSA and CP scripts for reference. Contents Python Bubble Sort Insertion Sort Merge Sort Quick So

Aditya Kumar Pandey 9 Nov 22, 2022
ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi-Object Segmentation

ClevrTex This repository contains dataset generation code for ClevrTex benchmark from paper: ClevrTex: A Texture-Rich Benchmark for Unsupervised Multi

Laurynas Karazija 26 Dec 21, 2022
Automatic Idiomatic Expression Detection

IDentifier of Idiomatic Expressions via Semantic Compatibility (DISC) An Idiomatic identifier that detects the presence and span of idiomatic expressi

5 Jun 09, 2022
Python package for visualizing the loss landscape of parameterized quantum algorithms.

orqviz A Python package for easily visualizing the loss landscape of Variational Quantum Algorithms by Zapata Computing Inc. orqviz provides a collect

Zapata Computing, Inc. 75 Dec 30, 2022
This is an early in-development version of training CLIP models with hivemind.

A transformer that does not hog your GPU memory This is an early in-development codebase: if you want a stable and documented hivemind codebase, look

<a href=[email protected]"> 4 Nov 06, 2022
一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM,xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,AFN,ONN,DIN, DIEN ... (pytorch, tf2.0)

CTR Algorithm 根据论文, 博客, 知乎等方式学习一些CTR相关的算法 理解原理并自己动手来实现一遍 pytorch & tf2.0 保持一颗学徒的心! Schedule Model pytorch tensorflow2.0 paper LR ✔️ ✔️ \ FM ✔️ ✔️ Fac

luo han 149 Dec 20, 2022
PyTorch Implementation of "Light Field Image Super-Resolution with Transformers"

LFT PyTorch implementation of "Light Field Image Super-Resolution with Transformers", arXiv 2021. [pdf]. Contributions: We make the first attempt to a

Squidward 62 Nov 28, 2022
A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval

CLIP4CMR A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval The original data and pre-calculate

24 Dec 26, 2022
A library for researching neural networks compression and acceleration methods.

A library for researching neural networks compression and acceleration methods.

Intel Labs 100 Dec 29, 2022
LoFTR:Detector-Free Local Feature Matching with Transformers CVPR 2021

LoFTR-with-train-script LoFTR:Detector-Free Local Feature Matching with Transformers CVPR 2021 (with train script --- unofficial ---). About Megadepth

Nan Xiaohu 15 Nov 04, 2022
automated systems to assist guarding corona Virus precautions for Closed Rooms (e.g. Halls, offices, etc..)

Automatic-precautionary-guard automated systems to assist guarding corona Virus precautions for Closed Rooms (e.g. Halls, offices, etc..) what is this

badra 0 Jan 06, 2022
Structure Information is the Key: Self-Attention RoI Feature Extractor in 3D Object Detection

Structure Information is the Key: Self-Attention RoI Feature Extractor in 3D Object Detection abstract:Unlike 2D object detection where all RoI featur

DK. Zhang 2 Oct 07, 2022
A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks

SVHNClassifier-PyTorch A PyTorch implementation of Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks If

Potter Hsu 182 Jan 03, 2023
A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval

CLIP4CMR A Comprehensive Empirical Study of Vision-Language Pre-trained Model for Supervised Cross-Modal Retrieval The original data and pre-calculate

24 Dec 26, 2022
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet

One Pixel Attack How simple is it to cause a deep neural network to misclassify an image if an attacker is only allowed to modify the color of one pix

Dan Kondratyuk 1.2k Dec 26, 2022
code for EMNLP 2019 paper Text Summarization with Pretrained Encoders

PreSumm This code is for EMNLP 2019 paper Text Summarization with Pretrained Encoders Updates Jan 22 2020: Now you can Summarize Raw Text Input!. Swit

Yang Liu 1.2k Dec 28, 2022
Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)

Python Streaming Anomaly Detection (PySAD) PySAD is an open-source python framework for anomaly detection on streaming multivariate data. Documentatio

Selim Firat Yilmaz 181 Dec 18, 2022