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Siamese Masked Autoencoders

NeurIPS 2023 · Video › Video segmentation and tracking · approach: Mask propagation for unsupervised video segmentation

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use asymmetric masking: leave the past frame unmasked and mask 95% of the future frame (ablation)SiamMAE · DAVISJ&F_m: 51.4 -> 58.1Helped
Increase asymmetric future-frame masking from 0.50 to 0.90 (ablation)SiamMAE · DAVISJ&F_m: 49.0 -> 58.4Helped
Use a siamese encoder instead of a joint encoder (ablation)SiamMAE with cross-self decoder · DAVISJ&F_m: 41.1 -> 58.1Helped
Use a cross-self decoder instead of a joint decoder (ablation)Siamese encoder · DAVISJ&F_m: 56.7 -> 58.1Helped
Use a cross-self decoder instead of a cross decoder (ablation)Siamese encoder · DAVISJ&F_m: 52.2 -> 58.1Helped
Add spatial augmentation (ablation)SiamMAE · DAVISJ&F_m: 56.8 -> 58.1Helped
Add color augmentation to spatial augmentation (ablation)SiamMAE · DAVISJ&F_m: 58.1 -> 56.7Hurt
Randomly sample frame gaps from 4-48 rather than use fixed gaps (ablation)SiamMAE · DAVISJ&F_m: 55.1 -> 58.1Helped
Use smaller ViT-S/8 patches rather than ViT-S/16 patchesSiamMAE · DAVIS-2017J&F_m: 62.0 -> 71.4Helped
Use SiamMAE rather than DINOViT-S/8 · VIPmIoU: 39.5 -> 45.9Helped
Use SiamMAE rather than VFSViT-S/8 vs ResNet-50 · JHMDBPCK@0.1: 60.9 -> 61.9Helped

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