- multi-GPU training for supervised models (#206)
- multi-GPU training for unsupervised models (#207)
- introduce jaxtyping (see here)
- incorporate transformer backbones (#84, #106)
- compute non-temporal unsupervised losses on labeled data
- implement supervised datasets/dataloaders that work with multiple views (#115)
- context frames for multi-view (#126)
- unsupervised losses for multi-view (#187)
- implement dynamic cropping pipeline with detector model and pose estimator
- context frames for dynamic crop
- unsupervised losses for dynamic crop
- perform view-specific dynamic cropping, re-assemble views after pose estimation stage
- context frames for multi-view dynamic crop
- unsupervised losses for multi-view dynamic crop
- single-view, supervised
- single-view, context
- single-view, unsupervised losses
- multi-view, supervised
- multi-view, context
- multi-view, unsupervised losses