Releases: lightly-ai/lightly
Releases · lightly-ai/lightly
Add SwaV Queue benchmarks on Imagenette
Changes
- Add SwaV Queue benchmarks on Imagenette
- Ability to pass dataset creator to Lightly API
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SimMIM: A Simple Framework for Masked Image Modeling, 2021
- SimSiam: Exploring Simple Siamese Representation Learning, 2020
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
- VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022
SwaV architecture docs
Changes
- Improved SwaV architecture documentation and an example
- Unit testing of frozen prototypes
- Gaussian blur implementation fix
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SimMIM: A Simple Framework for Masked Image Modeling, 2021
- SimSiam: Exploring Simple Siamese Representation Learning, 2020
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
- VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022
Better SSL schedulers, benchmarks for TiCo and VicRegl
Changes
- We added cosine decay for the DINO, BYOL, and MOCO models.
- We added a CosineWarmupScheduler class in the benchmarks.
- We added benchmark results for the TiCo and VICRegL models.
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SimMIM: A Simple Framework for Masked Image Modeling, 2021
- SimSiam: Exploring Simple Siamese Representation Learning, 2020
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
- VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022
Deprecate `lightly-upload`
Changes
- Deprecate dataset upload via CLI (
lightly-upload). In the future, only uploads with the Lightly Worker will be supported. - Add SimMIM and TiCo benchmarks.
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SimMIM: A Simple Framework for Masked Image Modeling, 2021
- SimSiam: Exploring Simple Siamese Representation Learning, 2020
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
- VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022
TiCo and VICRegL
Changes
- New TiCo model.
- New VICRegL model.
- API Client extended with list_datasource_permissions.
- Bug fix generalizing SMoGProjectionHead. Thanks @DrIsDr!
- Added version compatibility check.
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SimMIM: A Simple Framework for Masked Image Modeling, 2021
- SimSiam: Exploring Simple Siamese Representation Learning, 2020
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
- VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022
Contributors
DrIsDr
Assets 2
Prototype Freezing for SwaV
Changes
- Add SwAV prototype freezing. Thanks @ibro45 for the contribution!
- Add function to download embeddings.
- Update links in the README to point to the new docs.
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SimMIM: A Simple Framework for Masked Image Modeling, 2021
- SimSiam: Exploring Simple Siamese Representation Learning, 2020
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
Contributors
ibro45
Assets 2
Queue for SwAV
Changes
- Add queue implementation for SwAV. Thanks @ibro45 for the contribution!
- Fix memory bank initialization
- Fix API client version compatibility check
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SimMIM: A Simple Framework for Masked Image Modeling, 2021
- SimSiam: Exploring Simple Siamese Representation Learning, 2020
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
Contributors
ibro45
Assets 2
SimMIM
SimMIM
We added the SimMIM model. It has a very similar architecture to MAE, but it uses a ViT encoder using both masked and non-masked patches as input. Furthermore it has just a simple linear layer as a decoder and uses L1 instead of L2 loss.
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SimMIM, 2021
- SimSiam: Exploring Simple Siamese Representation Learning, 2020
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
Update API Client & Fix Citations
Changes
- Fix citations in README.md (Special thanks to @utkuozbulak)
- Update generated API code for Lightly API
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
Contributors
utkuozbulak
Assets 2
VICReg
Changes
- Added VICReg Model (Special thanks to Boris Albar @b-albar). (See VICReg example)
- The memory bank now works with distributed training.
- Speedup all code working with runs and datasets.
- Add helpers for predictions.
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
- MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
- MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
- 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
- SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
- SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
- VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
Contributors
b-albar