code for TCL: Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022

Overview

Vision-Language Pre-Training with Triple Contrastive Learning, CVPR 2022

News

(03/16/2022) upload retrieval checkpoints finetuned on COCO and Flickr


This is the official PyTorch implementation of TCL

image

Requirements:

conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=11.0 -c pytorch
pip install transformers==4.8.1
pip install timm==0.4.9
conda install ruamel_yaml
pip install opencv-python
pip install --upgrade Pillow
pip install einops

Pre-training Datasets:

Downstream-task Datasets:

Json Files from Pre-training and Downstream Tasks:

  • refer to Download in ALBEF
  • you need to change the image path in json files according to your downloaded images

Pre-trained checkpoint:

Pre-training:

python -m torch.distributed.launch --nproc_per_node=8 \
--use_env Pretrain.py \
--config ./configs/Pretrain.yaml \
--output_dir output/pretrain

Downstream Tasks:

Image-Text Retrieval

# zero-shot coco 
python -m torch.distributed.launch --nproc_per_node=8 \
--use_env Retrieval.py \
--config ./configs/Retrieval_coco.yaml \
--output_dir output/pretrain_e30_Retrieval_coco_zeroshot \
--checkpoint output/pretrain/checkpoint_29.pth \
--evaluate

# fine-tune flickr
python -m torch.distributed.launch --nproc_per_node=8 \
--use_env Retrieval.py \
--config ./configs/Retrieval_flickr.yaml \
--output_dir output/pretrain_e30_Retrieval_flickr \
--checkpoint output/pretrain/checkpoint_29.pth

# fine-tune coco
python -m torch.distributed.launch --nproc_per_node=8 \
--use_env Retrieval.py \
--config ./configs/Retrieval_coco.yaml \
--output_dir output/pretrain_e30_Retrieval_coco \
--checkpoint output/pretrain/checkpoint_29.pth

# zero-shot flickr 
python -m torch.distributed.launch --nproc_per_node=8 \
--use_env Retrieval.py \
--config ./configs/Retrieval_flickr.yaml \
--output_dir output/pretrain_e30_Retrieval_flickr_zeroshot \
--checkpoint output/pretrain_e30_Retrieval_coco/checkpoint_best.pth \
--evaluate

VQA

python -m torch.distributed.launch --nproc_per_node=8 \
--use_env VQA.py \
--config ./configs/VQA.yaml \
--output_dir output/pretrain_e30_vqa \
--checkpoint output/pretrain/checkpoint_29.pth

Visual Entailment

python -m torch.distributed.launch --nproc_per_node=8 \
--use_env VE.py \
--config ./configs/VE.yaml \
--output_dir output/pretrain_e30_VE \
--checkpoint output/pretrain/checkpoint_29.pth

NLVR2

# pre-train nlvr
python -m torch.distributed.launch --nproc_per_node=8 \
--use_env Pretrain_nlvr.py \
--config ./configs/NLVR_pretrain.yaml \
--output_dir output/pretrain_e30_NLVR_pretrain \
--checkpoint output/pretrain/checkpoint_29.pth

# fine-tune nlvr
python -m torch.distributed.launch --nproc_per_node=8 \
--use_env NLVR.py \
--config ./configs/NLVR.yaml \
--output_dir output/pretrain_e30_NLVR \
--checkpoint output/pretrain_e30_NLVR_pretrain/checkpoint_00.pth

Citation:

@article{yang2022vision,
  title={Vision-Language Pre-Training with Triple Contrastive Learning},
  author={Yang, Jinyu and Duan, Jiali and Tran, Son and Xu, Yi and Chanda, Sampath and Chen, Liqun and Zeng, Belinda and Chilimbi, Trishul and Huang, Junzhou},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  year={2022}
}

Our code is largely borrowed from ALBEF

Code for DeepCurrents: Learning Implicit Representations of Shapes with Boundaries

DeepCurrents | Webpage | Paper DeepCurrents: Learning Implicit Representations of Shapes with Boundaries David Palmer*, Dmitriy Smirnov*, Stephanie Wa

Dima Smirnov 36 Dec 08, 2022
Categorizing comments on YouTube into different categories.

Youtube Comments Categorization This repo is for categorizing comments on a youtube video into different categories. negative (grievances, complaints,

Rhitik 5 Nov 26, 2022
A faster pytorch implementation of faster r-cnn

A Faster Pytorch Implementation of Faster R-CNN Write at the beginning [05/29/2020] This repo was initaited about two years ago, developed as the firs

Jianwei Yang 7.1k Jan 01, 2023
Recreate CenternetV2 based on MMDET.

Introduction This project is trying to Recreate CenternetV2 based on MMDET, which is proposed in paper Probabilistic two-stage detection. This project

25 Dec 09, 2022
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages

DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program

Michihiro Yasunaga 155 Jan 08, 2023
City Surfaces: City-scale Semantic Segmentation of Sidewalk Surfaces

City Surfaces: City-scale Semantic Segmentation of Sidewalk Surfaces Paper Temporary GitHub page for City Surfaces paper. More soon! While designing s

14 Nov 10, 2022
Code for the paper "Benchmarking and Analyzing Point Cloud Classification under Corruptions"

ModelNet-C Code for the paper "Benchmarking and Analyzing Point Cloud Classification under Corruptions". For the latest updates, see: sites.google.com

Jiawei Ren 45 Dec 28, 2022
Snscrape-jsonl-urls-extractor - Extracts urls from jsonl produced by snscrape

snscrape-jsonl-urls-extractor extracts urls from jsonl produced by snscrape Usag

1 Feb 26, 2022
NeuroFind - A solution to the to the Task given by the Oberseminar of Messtechnik Institute of TU Dresden in 2021

NeuroFind A solution to the to the Task given by the Oberseminar of Messtechnik

1 Jan 20, 2022
Create animations for the optimization trajectory of neural nets

Animating the Optimization Trajectory of Neural Nets loss-landscape-anim lets you create animated optimization path in a 2D slice of the loss landscap

Logan Yang 81 Dec 25, 2022
Neural Point-Based Graphics

Neural Point-Based Graphics Project   Video   Paper Neural Point-Based Graphics Kara-Ali Aliev1 Artem Sevastopolsky1,2 Maria Kolos1,2 Dmitry Ulyanov3

Ali Aliev 252 Dec 13, 2022
An Inverse Kinematics library aiming performance and modularity

IKPy Demo Live demos of what IKPy can do (click on the image below to see the video): Also, a presentation of IKPy: Presentation. Features With IKPy,

Pierre Manceron 481 Jan 02, 2023
Official repo of the paper "Surface Form Competition: Why the Highest Probability Answer Isn't Always Right"

Surface Form Competition This is the official repo of the paper "Surface Form Competition: Why the Highest Probability Answer Isn't Always Right" We p

Peter West 46 Dec 23, 2022
Python package for downloading ECMWF reanalysis data and converting it into a time series format.

ecmwf_models Readers and converters for data from the ECMWF reanalysis models. Written in Python. Works great in combination with pytesmo. Citation If

TU Wien - Department of Geodesy and Geoinformation 31 Dec 26, 2022
Mercury: easily convert Python notebook to web app and share with others

Mercury Share your Python notebooks with others Easily convert your Python notebooks into interactive web apps by adding parameters in YAML. Simply ad

MLJAR 2.2k Dec 27, 2022
Image Data Augmentation in Keras

Image data augmentation is a technique that can be used to artificially expand the size of a training dataset by creating modified versions of images in the dataset.

Grace Ugochi Nneji 3 Feb 15, 2022
CTF Challenge for CSAW Finals 2021

Terminal Velocity Misc CTF Challenge for CSAW Finals 2021 This is a challenge I've had in mind for almost 15 years and never got around to building un

Jordan 6 Jul 30, 2022
Google AI Open Images - Object Detection Track: Open Solution

Google AI Open Images - Object Detection Track: Open Solution This is an open solution to the Google AI Open Images - Object Detection Track 😃 More c

minerva.ml 46 Jun 22, 2022
Bayesian Meta-Learning Through Variational Gaussian Processes

vmgp This is the repository of Vivek Myers and Nikhil Sardana for our CS 330 final project, Bayesian Meta-Learning Through Variational Gaussian Proces

Vivek Myers 2 Nov 17, 2022
Sum-Product Probabilistic Language

Sum-Product Probabilistic Language SPPL is a probabilistic programming language that delivers exact solutions to a broad range of probabilistic infere

MIT Probabilistic Computing Project 57 Nov 17, 2022