Alternatives and similar repositories for video_features

Users that are interested in video_features are comparing it to the libraries listed below

• happyharrycn / actionformer_release
  Code release for ActionFormer (ECCV 2022)
  ☆534Updated last year
• zhenyingfang / Awesome-Temporal-Action-Detection-Temporal-Action-Proposal-Generation
  Temporal Action Detection & Weakly Supervised Temporal Action Detection & Temporal Action Proposal Generation
  ☆566Updated last month
• cvdfoundation / kinetics-dataset
  ☆928Updated last year
• Finspire13 / pytorch-i3d-feature-extraction
  Code for I3D Feature Extraction
  ☆160Updated 6 years ago
• mx-mark / VideoTransformer-pytorch
  PyTorch implementation of a collections of scalable Video Transformer Benchmarks.
  ☆304Updated 3 years ago
• sallymmx / ActionCLIP
  This is the official implement of paper "ActionCLIP: A New Paradigm for Action Recognition"
  ☆597Updated 2 years ago
• rishikksh20 / ViViT-pytorch
  Implementation of ViViT: A Video Vision Transformer
  ☆556Updated 4 years ago
• v-iashin / BMT
  Source code for "Bi-modal Transformer for Dense Video Captioning" (BMVC 2020)
  ☆230Updated 2 years ago
• antoine77340 / video_feature_extractor
  Easy to use video deep features extractor
  ☆322Updated 5 years ago
• nus-cvml / awesome-temporal-action-segmentation
  A curated list of awesome temporal action segmentation resources.
  ☆235Updated last year
• OpenGVLab / VideoMAEv2
  [CVPR 2023] VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking
  ☆733Updated last year
• kylemin / S3D
  Release of the pretrained S3D Network in PyTorch (ECCV 2018)
  ☆136Updated 2 years ago
• okankop / vidaug
  Effective Video Augmentation Techniques for Training Convolutional Neural Networks
  ☆413Updated last year
• Alvin-Zeng / Awesome-Temporal-Action-Localization
  A curated list of temporal action localization/detection and related area (e.g. temporal action proposal) resources.
  ☆587Updated 3 years ago
• IBM / action-recognition-pytorch
  This is the pytorch implementation of some representative action recognition approaches including I3D, S3D, TSN and TAM.
  ☆257Updated 4 years ago
• TencentARC / UMT
  UMT is a unified and flexible framework which can handle different input modality combinations, and output video moment retrieval and/or …
  ☆233Updated last year
• ChinaYi / ASFormer
  Official repo for BMVC2021 paper ASFormer: Transformer for action segmentation
  ☆125Updated 3 years ago
• bomri / SlowFast
  PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
  ☆87Updated 4 years ago
• dingfengshi / TriDet
  [CVPR2023] Code for the paper, TriDet: Temporal Action Detection with Relative Boundary Modeling
  ☆205Updated 2 years ago
• danieljf24 / awesome-video-text-retrieval
  A curated list of deep learning resources for video-text retrieval.
  ☆641Updated 2 years ago
• jayleicn / moment_detr
  [NeurIPS 2021] Moment-DETR code and QVHighlights dataset
  ☆339Updated last year
• piergiaj / pytorch-i3d
  ☆1,033Updated 5 years ago
• Atze00 / MoViNet-pytorch
  MoViNets PyTorch implementation: Mobile Video Networks for Efficient Video Recognition;
  ☆289Updated 3 years ago
• RaivoKoot / Video-Dataset-Loading-Pytorch
  Generic PyTorch dataset implementation to load and augment VIDEOS for deep learning training loops.
  ☆470Updated 2 years ago
• sming256 / OpenTAD
  OpenTAD is an open-source temporal action detection (TAD) toolbox based on PyTorch.
  ☆313Updated 8 months ago
• ttengwang / PDVC
  End-to-End Dense Video Captioning with Parallel Decoding (ICCV 2021)
  ☆227Updated 2 years ago
• GowthamGottimukkala / I3D_Feature_Extraction_resnet
  I3D features extractor with resnet50 backbone
  ☆75Updated 3 years ago
• ArrowLuo / CLIP4Clip
  An official implementation for "CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval"
  ☆1,018Updated last year
• drv-agwl / ViViT-pytorch
  ☆69Updated 4 years ago
• baiyang4 / aqa_tpt
  implementation of "Action Quality Assessment with Temporal Parsing Transformer"
  ☆24Updated 3 years ago