Video Dataset initialisation improvements
Video Dataset initialisation speedup
When initialising a LightlyDataset on a directory with videos, all frames in all videos have to be counted to know the number of frames in the dataset and their filenames. This process now uses multihreading over videos and can thus be much faster.
Video Dataset initialisation bugfix
We fixed a bug that the number of frames was estimated wrongly based on the length of the video when using the pyav backend.
Video Dataset initialisation progress bar
When initialising the video dataset, a progress bar over the videos is shown. This is helpful information for datasets with many videos.
Models
- Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
- Bootstrap your own latent: A new approach to self-supervised Learning, 2020
- DCL: Decoupled Contrastive Learning, 2021
- DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
- MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
- NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
- SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
- SimSiam: Exploring Simple Siamese Representation Learning, 2020
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020