v0.3.0

This is a major update and introduces breaking changes to v0.2.
The list of changes below is not comprehensive, there may be other changes that are not listed.

Added

• New models:
  • DIP
  • Flow1D
  • FlowFormer++
  • GMFlow+
  • MatchFlow
  • MS-RAFT+
  • RPKNet
    -SeparableFlow
  • SKFlow
  • VideoFlow
• New datasets:
  • Middlebury
  • Monkaa
  • Spring
• Option to use RAFT's alt_cuda_corr for supported models
  • Also added a pure PyTorch version of alt_cuda_corr, which is slower but does not need to be compiled

Fixed

• Compatibility with PyTorch 2.0, 2.1
• Compatibility issues with PyTorch Lightning 1.9
• Resizing augmentation when the valid mask is sparse
• Models should produce results more similar to the paper
  • HOWEVER, we do not guarantee our results are correct. Use the official implementations for the most accurate results.

Changed

• Each model now handle its own IO reshaping, instead of using padding for all models
• speed_benchmark.py becomes model_benchmark.py and records more metrics
• Renamed model: pwcdcnet -> pwcnet, pwcnet -> pwcnet_nodc
• Updated requirements, support for many old versions are dropped
  • Important requirements:
    • python>=3.8,<3.12
    • torch>=1.13,<2.2
    • lightning>=1.9.0,<2