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}
}
PiRapGenerator - Make anyone rap the digits of pi

PiRapGenerator Make anyone rap the digits of pi (sample files are of Ted Nivison

7 Oct 02, 2022
Project page for our ICCV 2021 paper "The Way to my Heart is through Contrastive Learning"

The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video This is the official project page of our ICCV 2

36 Jan 06, 2023
Code for Two-stage Identifier: "Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition"

Code for Two-stage Identifier: "Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition", accepted at ACL 2021. For details of the model and experiments, please see our paper.

tricktreat 87 Dec 16, 2022
Discovering Interpretable GAN Controls [NeurIPS 2020]

GANSpace: Discovering Interpretable GAN Controls Figure 1: Sequences of image edits performed using control discovered with our method, applied to thr

Erik Härkönen 1.7k Jan 03, 2023
[ICML 2021] “ Self-Damaging Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang

Self-Damaging Contrastive Learning Introduction The recent breakthrough achieved by contrastive learning accelerates the pace for deploying unsupervis

VITA 51 Dec 29, 2022
This is the official implement of paper "ActionCLIP: A New Paradigm for Action Recognition"

This is an official pytorch implementation of ActionCLIP: A New Paradigm for Video Action Recognition [arXiv] Overview Content Prerequisites Data Prep

268 Jan 09, 2023
Reproducing code of hair style replacement method from Barbershorp.

Barbershorp Reproducing code of hair style replacement method from Barbershorp. Also reproduces II2S, an improved version of Image2StyleGAN. Requireme

1 Dec 24, 2021
[ICCV2021] Learning to Track Objects from Unlabeled Videos

Unsupervised Single Object Tracking (USOT) 🌿 Learning to Track Objects from Unlabeled Videos Jilai Zheng, Chao Ma, Houwen Peng and Xiaokang Yang 2021

53 Dec 28, 2022
SIEM Logstash parsing for more than hundred technologies

LogIndexer Pipeline Logstash Parsing Configurations for Elastisearch SIEM and OpenDistro for Elasticsearch SIEM Why this project exists The overhead o

146 Dec 29, 2022
deep learning model that learns to code with drawing in the Processing language

sketchnet sketchnet - processing code generator can we teach a computer to draw pictures with code. We use Processing and java/jruby code paired with

41 Dec 12, 2022
For holding anime-related object classification and detection models

Animesion An end-to-end framework for anime-related object classification, detection, segmentation, and other models. Update: 01/22/2020. Due to time-

Edwin Arkel Rios 72 Nov 30, 2022
A Closer Look at Structured Pruning for Neural Network Compression

A Closer Look at Structured Pruning for Neural Network Compression Code used to reproduce experiments in https://arxiv.org/abs/1810.04622. To prune, w

Bayesian and Neural Systems Group 140 Dec 05, 2022
Character Grounding and Re-Identification in Story of Videos and Text Descriptions

Character in Story Identification Network (CiSIN) This project hosts the code for our paper. Youngjae Yu, Jongseok Kim, Heeseung Yun, Jiwan Chung and

8 Dec 09, 2022
This repository contains all code and data for the Inside Out Visual Place Recognition task

Inside Out Visual Place Recognition This repository contains code and instructions to reproduce the results for the Inside Out Visual Place Recognitio

15 May 21, 2022
Here I will explain the flow to deploy your custom deep learning models on Ultra96V2.

Xilinx_Vitis_AI This repo will help you to Deploy your Deep Learning Model on Ultra96v2 Board. Prerequisites Vitis Core Development Kit 2019.2 This co

Amin Mamandipoor 1 Feb 08, 2022
Code repository for Semantic Terrain Classification for Off-Road Autonomous Driving

BEVNet Datasets Datasets should be put inside data/. For example, data/semantic_kitti_4class_100x100. Training BEVNet-S Example: cd experiments bash t

(Brian) JoonHo Lee 24 Dec 12, 2022
Pytorch implementation of "ARM: Any-Time Super-Resolution Method"

ARM-Net Dependencies Python 3.6 Pytorch 1.7 Results Train Data preprocessing cd data_scripts python extract_subimages_test.py python data_augmentation

Bohong Chen 55 Nov 24, 2022
Clustering is a popular approach to detect patterns in unlabeled data

Visual Clustering Clustering is a popular approach to detect patterns in unlabeled data. Existing clustering methods typically treat samples in a data

Tarek Naous 24 Nov 11, 2022
WORD: Revisiting Organs Segmentation in the Whole Abdominal Region

WORD: Revisiting Organs Segmentation in the Whole Abdominal Region (Paper and DataSet). [New] Note that all the emails about the download permission o

Healthcare Intelligence Laboratory 71 Dec 22, 2022
Histocartography is a framework bringing together AI and Digital Pathology

Documentation | Paper Welcome to the histocartography repository! histocartography is a python-based library designed to facilitate the development of

155 Nov 23, 2022