Moer Grounded Image Captioning by Distilling Image-Text Matching Model

Overview

Moer Grounded Image Captioning by Distilling Image-Text Matching Model

Requirements

  • Python 3.7
  • Pytorch 1.2

Prepare data

  1. Please use git clone --recurse-submodules to clone this repository and remember to follow initialization steps in coco-caption/README.md. Then download and place the Flickr30k reference file under coco-caption/annotations. Also, download Stanford CoreNLP 3.9.1 for grounding evaluation and place the uncompressed folder under the tools/ directory.
  2. Download the preprocessd dataset from this link and extract it to data/.
  3. For Flickr30k-Entities, please download bottom-up visual feature extracted by Anderson's extractor (Zhou's extractor) from this link ( link) and place the uncompressed folders under data/flickrbu/. For MSCOCO, please follow this instruction to prepare the bottom-up features and place them under data/mscoco/.
  4. Download the pretrained models from here and extract them to log/.
  5. Download the pretrained SCAN models from this link and extract them to misc/SCAN/runs.

Evaluation

To reproduce the results reported in the paper, just simply run

bash eval_flickr.sh

fro Flickr30k-Entities and

bash eval_coco.sh

for MSCOCO.

Training

  1. In the first training stage, run like
python train.py --id CE-scan-sup-0.1kl --caption_model topdown --input_json data/flickrtalk.json --input_fc_dir data/flickrbu/flickrbu_fc --input_att_dir data/flickrbu/flickrbu_att  --input_box_dir data/flickrbu/flickrbu_box  --input_label_h5 data/flickrtalk_label.h5 --batch_size 29 --learning_rate 5e-4 --learning_rate_decay_start 0 --scheduled_sampling_start 0 --checkpoint_path log/CE-scan-sup-0.1kl --save_checkpoint_every 1000 --val_images_use -1 --max_epochs 30  --att_supervise  True   --att_supervise_weight 0.1
  1. In the second training stage, run like
python train.py --id sc-ground-CE-scan-sup-0.1kl --caption_model topdown --input_json data/flickrtalk.json --input_fc_dir data/flickrbu/flickrbu_fc --input_att_dir data/flickrbu/flickrbu_att  --input_box_dir data/flickrbu/flickrbu_box  --input_label_h5 data/flickrtalk_label.h5 --batch_size 29 --learning_rate 5e-5 --start_from log/CE-scan-sup-0.1kl --checkpoint_path log/sc-ground-CE-scan-sup-0.1kl --save_checkpoint_every 1000 --language_eval 1 --val_images_use -1 --self_critical_after 30  --max_epochs  110      --cider_reward_weight  1
--ground_reward_weight   1 

Citation

@inproceedings{zhou2020grounded,
  title={More Grounded Image Captioning by Distilling Image-Text Matching Model},
  author={Zhou, Yuanen and Wang, Meng and Liu, Daqing and  Hu, Zhenzhen and Zhang, Hanwang},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  year={2020}
}

Acknowledgements

This repository is built upon self-critical.pytorch, SCAN and grounded-video-description. Thanks for their released code.

Owner
YE Zhou
YE Zhou
Mosaic of Object-centric Images as Scene-centric Images (MosaicOS) for long-tailed object detection and instance segmentation.

MosaicOS Mosaic of Object-centric Images as Scene-centric Images (MosaicOS) for long-tailed object detection and instance segmentation. Introduction M

Cheng Zhang 27 Oct 12, 2022
Definition of a business problem according to Wilson Lower Bound Score and Time Based Average Rating

Wilson Lower Bound Score, Time Based Rating Average In this study I tried to calculate the product rating and sorting reviews more accurately. I have

3 Sep 30, 2021
Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations

Trans-Encoder: Unsupervised sentence-pair modelling through self- and mutual-distillations Code repo for paper Trans-Encoder: Unsupervised sentence-pa

Amazon 101 Dec 29, 2022
An NVDA add-on to split screen reader and audio from other programs to different sound channels

An NVDA add-on to split screen reader and audio from other programs to different sound channels (add-on idea credit: Tony Malykh)

Joseph Lee 7 Dec 25, 2022
PyTorch EO aims to make Deep Learning for Earth Observation data easy and accessible to real-world cases and research alike.

Pytorch EO Deep Learning for Earth Observation applications and research. đźš§ This project is in early development, so bugs and breaking changes are ex

earthpulse 28 Aug 25, 2022
Semantic Segmentation of images using PixelLib with help of Pascalvoc dataset trained with Deeplabv3+ framework.

CARscan- Approach 1 - Segmentation of images by detecting contours. It failed because in images with elements along with cars were also getting detect

Padmanabha Banerjee 5 Jul 29, 2021
(JMLR'19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

Python Outlier Detection (PyOD) Deployment & Documentation & Stats Build Status & Coverage & Maintainability & License PyOD is a comprehensive and sca

Yue Zhao 6.6k Jan 03, 2023
Image marine sea litter prediction Shiny

MARLITE Shiny app for floating marine litter detection in aerial images. This directory contains the instructions and software needed to install the S

19 Dec 22, 2022
Microscopy Image Cytometry Toolkit

Cytokit Cytokit is a collection of tools for quantifying and analyzing properties of individual cells in large fluorescent microscopy datasets with a

Hammer Lab 106 Jan 06, 2023
Image Lowpoly based on Centroid Voronoi Diagram via python-opencv and taichi

CVTLowpoly: Image Lowpoly via Centroid Voronoi Diagram Image Sharp Feature Extraction using Guide Filter's Local Linear Theory via opencv-python. The

Pupa 4 Jul 29, 2022
Out-of-distribution detection using the pNML regret. NeurIPS2021

OOD Detection Load conda environment conda env create -f environment.yml or install requirements: while read requirement; do conda install --yes $requ

Koby Bibas 23 Dec 02, 2022
Tracking Pipeline helps you to solve the tracking problem more easily

Tracking_Pipeline Tracking_Pipeline helps you to solve the tracking problem more easily I integrate detection algorithms like: Yolov5, Yolov4, YoloX,

VNOpenAI 32 Dec 21, 2022
Contenido del curso Bases de datos del DCC PUC versiĂłn 2021-2

IIC2413 - Bases de Datos Tabla de contenidos Equipo Profesores Ayudantes Contenidos Calendario Evaluaciones Resumen de notas Foro PolĂ­tica de integrid

54 Nov 23, 2022
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and reinforcement learning

safe-control-gym Physics-based CartPole and Quadrotor Gym environments (using PyBullet) with symbolic a priori dynamics (using CasADi) for learning-ba

Dynamic Systems Lab 300 Dec 28, 2022
PyTorch implementation of PP-LCNet

PP-LCNet-Pytorch Pre-Trained Models Google Drive p018 Accuracy Models Top1 Top5 PPLCNet_x0_25 0.5186 0.7565 PPLCNet_x0_35 0.5809 0.8083 PPLCNet_x0_5 0

24 Dec 12, 2022
GPU-Accelerated Deep Learning Library in Python

Hebel GPU-Accelerated Deep Learning Library in Python Hebel is a library for deep learning with neural networks in Python using GPU acceleration with

Hannes Bretschneider 1.2k Dec 21, 2022
Official implementation of GraphMask as presented in our paper Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking.

GraphMask This repository contains an implementation of GraphMask, the interpretability technique for graph neural networks presented in our ICLR 2021

Michael Schlichtkrull 29 Sep 02, 2022
Unconstrained Text Detection with Box Supervisionand Dynamic Self-Training

SelfText Beyond Polygon: Unconstrained Text Detection with Box Supervisionand Dynamic Self-Training Introduction This is a PyTorch implementation of "

weijiawu 34 Nov 09, 2022
Tensorflow Tutorials using Jupyter Notebook

Tensorflow Tutorials using Jupyter Notebook TensorFlow tutorials written in Python (of course) with Jupyter Notebook. Tried to explain as kindly as po

Sungjoon 2.6k Dec 22, 2022
paper list in the area of reinforcenment learning for recommendation systems

paper list in the area of reinforcenment learning for recommendation systems

HenryZhao 23 Jun 09, 2022