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Documentation

  • Requesting An Account
  • Quick Start
  • Cluster Specifications
    • Node Features (Constraints)
      • NVLink and NVSwitch
    • Node List
    • Partition List
      • Gypsum
    • Storage
  • Frequently Asked Questions
  • Connecting to Unity
    • SSH
    • Unity OnDemand
    • Connecting to Desktop VS Code
  • Managing Files
    • Command Line Interface (CLI)
    • Disk Quotas
    • FileZilla
    • Globus
    • Scratch: HPC Workspace
    • Unity OnDemand File Browser
  • Submitting Jobs
    • Batch Jobs
      • Array Batch Jobs
      • Large Job Counts
      • Monitor a batch job
    • Helper Scripts
    • Interactive CLI Jobs
    • Unity OnDemand
    • Message Passing Interface (MPI)
    • Slurm cheat sheet
  • Software Management
    • Conda
    • Modules
      • Module Usage
    • Renv
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    • Venv
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      • R Parallelization
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      • DeepSeek
      • DINO v2
      • epic-kitchens
      • florence
      • gemma
      • gpt
      • gte-Qwen2
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      • Idefics2
      • Imagenet 1K
      • inaturalist
      • infly
      • instruct-blip
      • intfloat
      • LAION
      • linq
      • llama
      • Llama2
      • llama3
      • llama4
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      • Lumina
      • mixtral
      • msmarco
      • natural-questions
      • objaverse
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      • pythia
      • qwen
      • R1-1776
      • rag-sequence-nq
      • red-pajama-v2
      • s1-32B
      • satlas_pretrain
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      • NCBI RefSeq database
      • params
      • PDB70
      • PDB70 for ColabFold
      • PINDER
      • PLINDER
      • Protein Data Bank
      • Protein Data Bank database in mmCIF format
      • Protein Data Bank database in SEQRES records
      • Tara Oceans 18S amplicon
      • Tara Oceans MATOU gene catalog
      • Tara Oceans MGT transcriptomes
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      • UniRef100
      • UniRef30
      • UniRef90
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  1. Unity
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  5. video-MAE

video-MAE

Path:/datasets/ai/opengvlab
URL:https://huggingface.co/collections/OpenGVLab/videomae-v2-678631493ab2f0c4642d842d
Downloaded:07-03-2025
Cite:Wang, Limin, et al. “Videomae v2: Scaling video masked autoencoders with dual masking.” Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2023.
Variant:
    Bibtex:
    @InProceedings{Wang_2023_CVPR,
        author    = {Wang, Limin and Huang, Bingkun and Zhao, Zhiyu and Tong, Zhan and He, Yinan and Wang, Yi and Wang, Yali and Qiao, Yu},
        title     = {VideoMAE V2: Scaling Video Masked Autoencoders With Dual Masking},
        booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
        month     = {June},
        year      = {2023},
        pages     = {14549-14560}
    }
    Last modified: Monday, April 7, 2025 at 10:35 AM. See the commit on GitLab.
    University of Massachusetts Amherst University of Massachusetts Amherst University of Rhode Island University of Rhode Island University of Massachusetts Dartmouth University of Massachusetts Dartmouth University of Massachusetts Lowell University of Massachusetts Lowell University of Massachusetts Boston University of Massachusetts Boston Mount Holyoke College Mount Holyoke College
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