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Research map / Probabilistic and scientific modeling / Molecules and proteins

DDFlow: Learning Optical Flow with Unlabeled Data Distillation

AAAI 2019 · Probabilistic and scientific modeling › Molecules and proteins · approach: Flow matching generative modeling · 174 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Distill teacher flow predictions to supervise cropped-patch occlusions (ablation)DDFlow · Flying Chairs testEPE: 3.24 -> 2.97Helped
Add occlusion handling (ablation)DDFlow without census or distillation · Flying Chairs testEPE: 4.06 -> 3.95Helped
Add occlusion handling (ablation)DDFlow with census transform and without distillation · Flying Chairs testEPE: 3.75 -> 3.24Helped
Add census transform (ablation)DDFlow without occlusion handling or distillation · Flying Chairs testEPE: 4.06 -> 3.75Helped
Add census transform (ablation)DDFlow with occlusion handling and without distillation · Flying Chairs testEPE: 3.95 -> 3.24Helped
Add data distillation (ablation)DDFlow with occlusion handling and census transform · Sintel Clean trainEPE OCC: 29.36 -> 23.92Helped
Add data distillation (ablation)DDFlow with occlusion handling and census transform · Sintel Final trainEPE OCC: 31.86 -> 26.74Helped
Add data distillation (ablation)DDFlow with occlusion handling and census transform · KITTI 2012 trainEPE OCC: 27.04 -> 11.31Helped
Add data distillation (ablation)DDFlow with occlusion handling and census transform · KITTI 2015 trainEPE OCC: 42.66 -> 24.68Helped
Fine-tune DDFlow on Sintel training dataDDFlow pretrained on Flying Chairs · Sintel Clean testEPE: 7.23 -> 6.18Helped
Fine-tune DDFlow on Sintel training dataDDFlow pretrained on Flying Chairs · Sintel Final testEPE: 8.81 -> 7.40Helped
Use DDFlow instead of the strongest reported unsupervised comparatorOptical flow estimation · Flying Chairs testEPE: 3.30 -> 2.97Helped

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