Negative Sample is Negative in Its Own Way: Tailoring Negative Sentences forImage-Text Retrieval

Related tags

Deep LearningTAGS
Overview

NSGDC

Some codes in this repo are copied/modified from opensource implementations made available by UNITER, PyTorch, HuggingFace, OpenNMT, and Nvidia. The image features are extracted using BUTD.

Requirements

This is following UNITER. We provide Docker image for easier reproduction. Please install the following:

Our scripts require the user to have the docker group membership so that docker commands can be run without sudo. We only support Linux with NVIDIA GPUs. We test on Ubuntu 18.04 and V100 cards. We use mixed-precision training hence GPUs with Tensor Cores are recommended.

Image-Text Retrieval

Download Data

bash scripts/download_itm.sh $PATH_TO_STORAGE

Launch the Docker Container

# docker image should be automatically pulled
source launch_container.sh $PATH_TO_STORAGE/txt_db $PATH_TO_STORAGE/img_db \
$PATH_TO_STORAGE/finetune $PATH_TO_STORAGE/pretrained

In case you would like to reproduce the whole preprocessing pipeline.

The launch script respects $CUDA_VISIBLE_DEVICES environment variable. Note that the source code is mounted into the container under /src instead of built into the image so that user modification will be reflected without re-building the image. (Data folders are mounted into the container separately for flexibility on folder structures.)

Image-Text Retrieval (Flickr30k)

# Train wit the base setting
bash run_cmds/tran_pnsgd_base_flickr.sh
bash run_cmds/tran_pnsgd2_base_flickr.sh

# Train wit the large setting
bash run_cmds/tran_pnsgd_large_flickr.sh
bash run_cmds/tran_pnsgd2_large_flickr.sh

Image-Text Retrieval (COCO)

# Train wit the base setting
bash run_cmds/tran_pnsgd_base_coco.sh
bash run_cmds/tran_pnsgd2_base_coco.sh

# Train wit the large setting
bash run_cmds/tran_pnsgd_large_coco.sh
bash run_cmds/tran_pnsgd2_large_coco.sh

Run Inference

bash run_cmds/inf_nsgd.sh

Results

Our models achieve the following performance.

MS-COCO

Model Image-to-Text Text-to-Image
[email protected] [email protected] [email protected] [email protected] [email protected] [email protected]
NSGDC-Base 66.6 88.6 94.0 51.6 79.1 87.5
NSGDC-Large 67.8 89.6 94.2 53.3 80.0 88.0

Flickr30K

Model Image-to-Text Text-to-Image
[email protected] [email protected] [email protected] [email protected] [email protected] [email protected]
NSGDC-Base 87.9 98.1 99.3 74.5 93.3 96.3
NSGDC-Large 90.6 98.8 99.1 77.3 94.3 97.3
Owner
Zhihao Fan
Zhihao Fan
A keras-based real-time model for medical image segmentation (CFPNet-M)

CFPNet-M: A Light-Weight Encoder-Decoder Based Network for Multimodal Biomedical Image Real-Time Segmentation This repository contains the implementat

268 Nov 27, 2022
Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"

Topographic Variational Autoencoder Paper: https://arxiv.org/abs/2109.01394 Getting Started Install requirements with Anaconda: conda env create -f en

T. Andy Keller 69 Dec 12, 2022
My personal Home Assistant configuration.

About This is my personal Home Assistant configuration. My guiding princile is to have full local control of all my devices. I intend everything to ru

Chris Turra 13 Jun 07, 2022
An Efficient Implementation of Analytic Mesh Algorithm for 3D Iso-surface Extraction from Neural Networks

AnalyticMesh Analytic Marching is an exact meshing solution from neural networks. Compared to standard methods, it completely avoids geometric and top

Karbo 45 Dec 21, 2022
这是一个facenet-pytorch的库,可以用于训练自己的人脸识别模型。

Facenet:人脸识别模型在Pytorch当中的实现 目录 性能情况 Performance 所需环境 Environment 注意事项 Attention 文件下载 Download 预测步骤 How2predict 训练步骤 How2train 参考资料 Reference 性能情况 训练数据

Bubbliiiing 210 Jan 06, 2023
Efficient Deep Learning Systems course

Efficient Deep Learning Systems This repository contains materials for the Efficient Deep Learning Systems course taught at the Faculty of Computer Sc

Max Ryabinin 173 Dec 29, 2022
A Comprehensive Study on Learning-Based PE Malware Family Classification Methods

A Comprehensive Study on Learning-Based PE Malware Family Classification Methods Datasets Because of copyright issues, both the MalwareBazaar dataset

8 Oct 21, 2022
Makes patches from huge resolution .svs slide files using openslide

openslide_patcher Makes patches from huge resolution .svs slide files using openslide Example collage I made from outputs:

2 Dec 23, 2021
WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution

WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution This code belongs to the paper [1] available at https://arx

Fabian Altekrueger 5 Jun 02, 2022
PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Condition Layer Normalization and Semi-Supervised Training in Text-To-Speech

Cross-Speaker-Emotion-Transfer - PyTorch Implementation PyTorch Implementation of ByteDance's Cross-speaker Emotion Transfer Based on Speaker Conditio

Keon Lee 114 Jan 08, 2023
Multi-scale discriminator feature-wise loss function

Multi-Scale Discriminative Feature Loss This repository provides code for Multi-Scale Discriminative Feature (MDF) loss for image reconstruction algor

Graphics and Displays group - University of Cambridge 76 Dec 12, 2022
Spatial Contrastive Learning for Few-Shot Classification (SCL)

This repo contains the official implementation of Spatial Contrastive Learning for Few-Shot Classification (SCL), which presents of a novel contrastive learning method applied to few-shot image class

Yassine 34 Dec 25, 2022
The repository offers the official implementation of our BMVC 2021 paper in PyTorch.

CrossMLP Cascaded Cross MLP-Mixer GANs for Cross-View Image Translation Bin Ren1, Hao Tang2, Nicu Sebe1. 1University of Trento, Italy, 2ETH, Switzerla

Bingoren 16 Jul 27, 2022
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond

BasicVSR BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond Ported from https://github.com/xinntao/BasicSR Dependencie

Holy Wu 8 Jun 07, 2022
Single object tracking and segmentation.

Single/Multiple Object Tracking and Segmentation Codes and comparison of recent single/multiple object tracking and segmentation. News 💥 AutoMatch is

ZP ZHANG 385 Jan 02, 2023
Download and preprocess popular sequential recommendation datasets

Sequential Recommendation Datasets This repository collects some commonly used sequential recommendation datasets in recent research papers and provid

125 Dec 06, 2022
Uses Open AI Gym environment to create autonomous cryptocurrency bot to trade cryptocurrencies.

Crypto_Bot Uses Open AI Gym environment to create autonomous cryptocurrency bot to trade cryptocurrencies. Steps to get started using the bot: Sign up

21 Oct 03, 2022
In-Place Activated BatchNorm for Memory-Optimized Training of DNNs

In-Place Activated BatchNorm In-Place Activated BatchNorm for Memory-Optimized Training of DNNs In-Place Activated BatchNorm (InPlace-ABN) is a novel

1.3k Dec 29, 2022
Pytorch implementation of CVPR2021 paper "MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generation"

MUST-GAN Code | paper The Pytorch implementation of our CVPR2021 paper "MUST-GAN: Multi-level Statistics Transfer for Self-driven Person Image Generat

TianxiangMa 46 Dec 26, 2022
Python implementation of the multistate Bennett acceptance ratio (MBAR)

pymbar Python implementation of the multistate Bennett acceptance ratio (MBAR) method for estimating expectations and free energy differences from equ

Chodera lab // Memorial Sloan Kettering Cancer Center 169 Dec 02, 2022