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dynadust3r-unofficial-weights

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Add unofficial DynaDUSt3R .pth weights + model card

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Files changed (24) hide show
  1. .gitattributes +1 -0
  2. README.md +45 -0
  3. SHA256SUMS.txt +21 -0
  4. best_loss_0.367080_iter_34000_epoch_17.pth +3 -0
  5. best_loss_0.386052_iter_38000_epoch_19.pth +3 -0
  6. best_loss_0.392713_iter_94000_epoch_47.pth +3 -0
  7. best_loss_0.396031_iter_32000_epoch_16.pth +3 -0
  8. best_loss_0.427555_iter_24000_epoch_12.pth +3 -0
  9. best_loss_0.427857_iter_92000_epoch_46.pth +3 -0
  10. best_loss_0.431392_iter_52000_epoch_26.pth +3 -0
  11. best_loss_0.443512_iter_88000_epoch_44.pth +3 -0
  12. best_loss_0.468565_iter_58000_epoch_29.pth +3 -0
  13. best_loss_0.478208_iter_56000_epoch_28.pth +3 -0
  14. best_loss_0.480609_iter_40000_epoch_20.pth +3 -0
  15. best_loss_0.480798_iter_90000_epoch_45.pth +3 -0
  16. best_loss_0.482799_iter_86000_epoch_43.pth +3 -0
  17. best_loss_0.493017_iter_66000_epoch_33.pth +3 -0
  18. best_loss_0.499884_iter_26000_epoch_13.pth +3 -0
  19. best_loss_0.503958_iter_82000_epoch_41.pth +3 -0
  20. best_loss_0.523247_iter_42000_epoch_21.pth +3 -0
  21. best_loss_0.525647_iter_28000_epoch_14.pth +3 -0
  22. best_loss_0.527959_iter_30000_epoch_15.pth +3 -0
  23. best_loss_0.528999_iter_60000_epoch_30.pth +3 -0
  24. last_iter_98000_epoch_49.pth +3 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ *.pth filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ # DynaDUSt3R (Unofficial) — Model Weights
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+
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+ This repository hosts PyTorch `.pth` checkpoint files for the **DynaDUSt3R** model — an external, unofficial reimplementation of the model proposed in the paper [*Stereo4D: Learning How Things Move in 3D from Internet Stereo Videos*](https://arxiv.org/abs/2412.09621) by Linyi Jin, Richard Tucker, Zhengqi Li, David Fouhey, Noah Snavely, and Aleksander Hołyński.
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+
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+ ---
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+
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+ ## Overview
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+
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+ DynaDUSt3R extends [DUSt3R](https://openaccess.thecvf.com/content/CVPR2024/papers/Wang_DUSt3R_Geometric_3D_Vision_Made_Easy_CVPR_2024_paper.pdf) to dynamic scenes by predicting per-pixel 3D points and 3D motion trajectories from stereo video sequences.
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+ These weights were obtained from an independent reimplementation and are provided solely for research and reproducibility purposes.
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+
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+ The accompanying codebase can be found in the [dynadust3r-unofficial](https://github.com/KevinMathewT/dynadust3r-unofficial) repository.
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+ Instructions for running inference are available in the [inference example script](https://github.com/KevinMathewT/dynadust3r-unofficial/blob/main/infer/infer_example.py).
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+
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+ ---
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+
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+ ## Contents
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+
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+ - `.pth` checkpoint files corresponding to trained DynaDUSt3R models.
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+ - Optional `SHA256SUMS.txt` for integrity verification.
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+
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+ These checkpoints are compatible with the model definitions in the [dynadust3r-unofficial](https://github.com/KevinMathewT/dynadust3r-unofficial) repository.
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+
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+ ---
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+
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+ ## Usage
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+
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+ Please follow the setup and inference steps described in the main [dynadust3r-unofficial](https://github.com/KevinMathewT/dynadust3r-unofficial) repository.
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+ The weights can be loaded using `torch.load()` as shown in the [inference example](https://github.com/KevinMathewT/dynadust3r-unofficial/blob/main/infer/infer_example.py).
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+
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+ **Note:** `.pth` files use Python pickle and should only be loaded from trusted sources.
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+
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+ ---
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+
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+ ## References
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+
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+ - [Stereo4D Project Page](https://stereo4d.github.io/)
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+ - [DUSt3R Paper (CVPR 2024)](https://openaccess.thecvf.com/content/CVPR2024/papers/Wang_DUSt3R_Geometric_3D_Vision_Made_Easy_CVPR_2024_paper.pdf)
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+
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+ ---
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+
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+ ## License
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+
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+ These weights are provided for research and non-commercial use only.
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+ This repository is **unofficial** and not affiliated with the authors of *Stereo4D*.
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