GithubHelp home page GithubHelp logo

amrahsmaytas / awesome-video-text-retrieval Goto Github PK

View Code? Open in Web Editor NEW

This project forked from danieljf24/awesome-video-text-retrieval

0.0 0.0 0.0 14 KB

A curated list of deep learning resources for video-text retrieval.

awesome-video-text-retrieval's Introduction

Awesome Video-Text Retrieval by Deep Learning Awesome

A curated list of deep learning resources for video-text retrieval.

Contributing

Please feel free to pull requests to add papers.

Markdown format:

- `[Author Journal/Booktitle Year]` Title. Journal/Booktitle, Year. [[paper]](link) [[code]](link) [[homepage]](link)

Table of Contents

Implementations

PyTorch

TensorFlow

Others

Papers

2020

  • [Dong et al. ARXIV20] Hybrid Space Learning for Language-based Video Retrieval. arXiv:2009.05381, 2020. [paper] [code]
  • [Yang et al. SIGIR20] Tree-Augmented Cross-Modal Encoding for Complex-Query Video Retrieval. SIGIR, 2020. [paper]
  • [Gabeur et al. ECCV20] Multi-modal Transformer for Video Retrieval. ECCV, 2020. [paper]
  • [Wang et al. TMM20] Learning Coarse-to-Fine Graph Neural Networks for Video-Text Retrieval. IEEE Transactions on Multimedia, 2020. [paper]
  • [Wu et al. ACMMM20] Interpretable Embedding for Ad-Hoc Video Search. ACM Multimedia, 2020. [paper]
  • [Doughty et al. CVPR20] Action Modifiers: Learning from Adverbs in Instructional Videos. CVPR, 2020. [paper]
  • [Chen et al. CVPR20] Fine-grained Video-Text Retrieval with Hierarchical Graph Reasoning. CVPR, 2020. [paper]
  • [Zhu et al. CVPR20] ActBERT: Learning Global-Local Video-Text Representations. CVPR, 2020. [paper]

2019

  • [Dong et al. CVPR19] Dual Encoding for Zero-Example Video Retrieval. CVPR, 2019. [paper] [code]
  • [Song et al. CVPR19] Polysemous visual-semantic embedding for cross-modal retrieval. CVPR, 2019. [paper]
  • [Wray et al. ICCV19] Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings. ICCV, 2019. [paper]
  • [Xiong et al. ICCV19] A Graph-Based Framework to Bridge Movies and Synopses. ICCV, 2019. [paper]
  • [Li et al. ACMMM19] W2VV++ Fully Deep Learning for Ad-hoc Video Search. ACM Multimedia, 2019. [paper] [code]
  • [Liu et al. BMVC19] Use What You Have: Video Retrieval Using Representations From Collaborative Experts. MBVC, 2019. [paper] [code]
  • [Choi et al. BigMM19] From Intra-Modal to Inter-Modal Space: Multi-Task Learning of Shared Representations for Cross-Modal Retrieval. International Conference on Multimedia Big Data, 2019. [paper]

2018

  • [Dong et al. TMM18] Predicting visual features from text for image and video caption retrieval. IEEE Transactions on Multimedia, 2018. [paper] [code]
  • [Zhang et al. ECCV18] Cross-Modal and Hierarchical Modeling of Video and Text. ECCV, 2018. [paper] [code]
  • [Yu et al. ECCV18] A Joint Sequence Fusion Model for Video Question Answering and Retrieval. ECCV, 2018. [paper]
  • [Shao et al. ECCV18] Find and focus: Retrieve and localize video events with natural language queries. ECCV, 2018. [paper]
  • [Mithun et al. ICMR18] Learning Joint Embedding with Multimodal Cues for Cross-Modal Video-Text Retrieval. ICMR, 2018. [paper] [code]
  • [Miech et al. arXiv18] Learning a Text-Video Embedding from Incomplete and Heterogeneous Data. arXiv preprint arXiv:1804.02516, 2018. [paper] [code]

Before

  • [Yu et al. CVPR17] End-to-end concept word detection for video captioning, retrieval, and question answering. CVPR, 2017. [paper] [code]
  • [OtaniEmail et al. ECCVW2016] Learning joint representations of videos and sentences with web image search. ECCV Workshop, 2016. [paper]
  • [Xu et al. AAAI15] Jointly modeling deep video and compositional text to bridge vision and language in a unified framework. AAAI, 2015. [paper]

Ad-hoc Video Search

  • For the papers targeting at ad-hoc video search in the context of TRECVID, please refer to here.

Other Related

  • [Li et al. arXiv20] Learning Spatiotemporal Features via Video and Text Pair Discrimination. arXiv preprint arXiv:2001.05691, 2020. [paper]
  • [Miech et al. CVPR20] End-to-End Learning of Visual Representations from Uncurated Instructional Videos. CVPR, 2020. [paper]

Datasets

  • [MSVD] David et al. Collecting Highly Parallel Data for Paraphrase Evaluation. ACL, 2011. [paper] [dataset]
  • [MSRVTT] Xu et al. MSR-VTT: A Large Video Description Dataset for Bridging Video and Language. CVPR, 2016. [paper] [dataset]
  • [TGIF] Li et al. TGIF: A new dataset and benchmark on animated GIF description. CVPR, 2016. [paper] [homepage]
  • [AVS] Awad et al. Trecvid 2016: Evaluating video search, video event detection, localization, and hyperlinking. TRECVID Workshop, 2016. [paper] [dataset]
  • [LSMDC] Rohrbach et al. Movie description. IJCV, 2017. [paper] [dataset]
  • [ActivityNet Captions] Krishna et al. Dense-captioning events in videos. ICCV, 2017. [paper] [dataset]
  • [DiDeMo] Hendricks et al. Localizing Moments in Video with Natural Language. ICCV, 2017. [paper] [code]
  • [HowTo100M] Miech et al. HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips. ICCV, 2019. [paper] [homepage]
  • [VATEX] Wang et al. VATEX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research. ICCV, 2019. [paper] [homepage]

Licenses

CC0

To the extent possible under law, danieljf24 all copyright and related or neighboring rights to this repository.

awesome-video-text-retrieval's People

Contributors

danieljf24 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.