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Python implementation of extraction of several visual features representations from videos

Python 70.41% Lua 1.35% Starlark 1.52% Shell 1.36% Jupyter Notebook 1.56% C++ 23.53% Makefile 0.23% Dockerfile 0.05%
visual-representation video-representation cnn c3d video-captioning msvd msr-vtt trecvid activitynet-captions vatex

video_features_extractor's Introduction

Video Features Extractor

Extracting several kinds of visual representations from videos.

Supported visual features

The following frame-level (*_features) and video-level (*_gloabal) visual representations are supported:

  1. 2D-CNN (cnn_features, cnn_globals, cnn_sem_globals)
  2. 3D-CNN (c3d_features, c3d_globals, i3d_features, i3d_globals)
  3. ECO (eco_features, eco_globals, eco_sem_features, eco_sem_globals)
  4. TSM (tsm_features, tsm_globals, tsm_sem_features, tsm_sem_globals)

Note: *_sem_* representations are based on the classification level (probability distribution) of respective models.

Supported Datasets

This package has been tested for extracting visual representations from videos of the following video-caption datasets:

  1. MSVD
  2. M-VAD
  3. MSR-VTT
  4. TRECVID-2020
  5. TRECVID-2020-Test
  6. TGIF
  7. VATEX
  8. ActivityNet
  9. ActivityNet-Test
  10. ActivityNet-Fragments

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