Use CLIP to represent video for Retrieval Task

Related tags

Deep Learning CLIP_Video_Representation
Overview

A Straightforward Framework For Video Retrieval Using CLIP

PWC

PWC

PWC

PWC

This repository contains the basic code for feature extraction and replication of results.

this work has been submitted to the Mexican Conference of Pattern Recognition (MCPR 2021).

If you consider this work useful please cite as:

@misc{portilloquintero2021straightforward,
      title={A Straightforward Framework For Video Retrieval Using CLIP}, 
      author={Jesús Andrés Portillo-Quintero and José Carlos Ortiz-Bayliss and Hugo Terashima-Marín},
      year={2021},
      eprint={2102.12443},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
You might also like...
[2021 MultiMedia] CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval
[2021 MultiMedia] CONQUER: Contextual Query-aware Ranking for Video Corpus Moment Retrieval

CONQUER: Contexutal Query-aware Ranking for Video Corpus Moment Retreival PyTorch implementation of CONQUER: Contexutal Query-aware Ranking for Video

Hou zhijian 23 Dec 26, 2022
Fake videos detection by tracing the source using video hashing retrieval.
Fake videos detection by tracing the source using video hashing retrieval.

Vision Transformer Based Video Hashing Retrieval for Tracing the Source of Fake Videos 🎉️ 📜 Directory Introduction VTL Trace Samples and Acc of Hash

null 56 Dec 22, 2022
Near-Duplicate Video Retrieval with Deep Metric Learning
Near-Duplicate Video Retrieval with Deep Metric Learning

Near-Duplicate Video Retrieval with Deep Metric Learning This repository contains the Tensorflow implementation of the paper Near-Duplicate Video Retr

null 2 Jan 24, 2022
[arXiv22] Disentangled Representation Learning for Text-Video Retrieval
[arXiv22] Disentangled Representation Learning for Text-Video Retrieval

Disentangled Representation Learning for Text-Video Retrieval This is a PyTorch implementation of the paper Disentangled Representation Learning for T

Qiang Wang 49 Dec 18, 2022
UMT is a unified and flexible framework which can handle different input modality combinations, and output video moment retrieval and/or highlight detection results.

Unified Multi-modal Transformers This repository maintains the official implementation of the paper UMT: Unified Multi-modal Transformers for Joint Vi

Applied Research Center (ARC), Tencent PCG 84 Jan 4, 2023
Video-Captioning - A machine Learning project to generate captions for video frames indicating the relationship between the objects in the video
Video-Captioning - A machine Learning project to generate captions for video frames indicating the relationship between the objects in the video

Video-Captioning - A machine Learning project to generate captions for video frames indicating the relationship between the objects in the video

null 1 Jan 23, 2022
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain

Unity Technologies 187 Dec 24, 2022
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)

Deep Daze mist over green hills shattered plates on the grass cosmic love and attention a time traveler in the crowd life during the plague meditative

Phil Wang 4.4k Jan 3, 2023
Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search

CLIP-GLaSS Repository for the paper Generating images from caption and vice versa via CLIP-Guided Generative Latent Space Search An in-browser demo is

Federico Galatolo 172 Dec 22, 2022
Comments
  • Training Data Features

    Training Data Features

    Hey, do you also have the precomputed training video and text features for MSRVTT and MSVD ? It would be really helpful if you can upload them. Thanks in advance.

    opened by ra1ph2 0
Owner
Jesus Andres Portillo Quintero
Jesus Andres Portillo Quintero
GitHub
FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization

FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat

XCL 191 Dec 31, 2022
CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP

CLIP-GEN [简体中文][English] 本项目在萤火二号集群上用 PyTorch 实现了论文 《CLIP-GEN: Language-Free Training of a Text-to-Image Generator with CLIP》。 CLIP-GEN 是一个 Language-F

null 75 Dec 29, 2022
Image-retrieval-baseline - MUGE Multimodal Retrieval Baseline

MUGE Multimodal Retrieval Baseline This repo is implemented based on the open_cl

null 47 Dec 16, 2022
Apply AnimeGAN-v2 across frames of a video clip

title emoji colorFrom colorTo sdk app_file pinned AnimeGAN-v2 For Videos ?? blue red gradio app.py false AnimeGAN-v2 For Videos Apply AnimeGAN-v2 acro

Nathan Raw 36 Oct 18, 2022
Making a music video with Wav2CLIP and VQGAN-CLIP

music2video Overview A repo for making a music video with Wav2CLIP and VQGAN-CLIP. The base code was derived from VQGAN-CLIP The CLIP embedding for au

Joel Jang | 장요엘 163 Dec 26, 2022
Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

Nerdy Rodent 2.3k Jan 4, 2023
Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab.

CLIP-Guided-Diffusion Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab. Original colab notebooks by Ka

Nerdy Rodent 336 Dec 9, 2022
Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab

VQGAN-CLIP-Video cat.mp4 policeman.mp4 schoolboy.mp4 forsenBOG.mp4

null 23 Oct 26, 2022
Activity image-based video retrieval

Cross-modal-retrieval Our approach is focus on Activity Image-to-Video Retrieval (AIVR) task. The compared methods are state-of-the-art single modalit

BCMI 75 Oct 21, 2021
A Joint Video and Image Encoder for End-to-End Retrieval

Frozen️ in Time ❄️ ️️️️ ⏳ A Joint Video and Image Encoder for End-to-End Retrieval project page | arXiv | webvid-data Repository containing the code,

null 225 Dec 25, 2022