Motion energy features from video
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Updated
Jul 29, 2024 - Python
Motion energy features from video
deep_video_extraction is a powerful repository designed to extract deep feature representations from video inputs using pre-trained models. With support for both visual and aural features from videos. Additionally, you can process audio separately by converting it into spectrograms.
Source code for "Taming Visually Guided Sound Generation" (Oral at the BMVC 2021)
Extract video features from raw videos using multiple GPUs. We support RAFT flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, and TIMM models.
A simple motion extraction for video inspired from posy
Source code for "Bi-modal Transformer for Dense Video Captioning" (BMVC 2020)
Video Feature Extraction Code for EMNLP 2020 paper "HERO: Hierarchical Encoder for Video+Language Omni-representation Pre-training"
Feature Extractor module for videos using the PySlowFast framework
Video feature extractor in PyTorch.
Repository with code to extract different features from video and images.
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