Phase Marginalization Addresses Patch-Grid Instability in Vision Transformers
Researchers propose Phase Marginalization, a post-hoc method to reduce instability in Vision Transformers caused by fixed patch grids affecting dense prediction tasks. The technique evaluates multiple patch-grid configurations and aggregates outputs without requiring retraining. The method shows modest but consistent improvements in segmentation, depth estimation, and matching tasks, with practical efficiency gains at K=4 patch configurations.
Vision Transformers process images by dividing them into fixed patch grids, but this approach introduces phase-dependent instability where changing the patch partition alters which tokens are available to predict values for pixels, particularly near boundaries. The authors formalize patch-grid phase as a nuisance variable and introduce Phase Marginalization, a training-free post-hoc method that evaluates multiple structured patch-grid phases, inverse-aligns the resulting dense outputs, and aggregates them in the original image coordinate system. Testing on Cityscapes segmentation shows Uniform Phase Marginalization with K=4 provides a +0.31 mean Intersection-over-Union improvement over the baseline single-phase approach and outperforms generic shift-based test-time augmentation. A scaling study indicates K=4 represents an optimal cost-accuracy trade-off, with K=8 showing minimal additional gains and K=16 adding negligible accuracy at substantially higher computational cost. The work positions patch-grid phase as a measurable and addressable source of instability in dense ViT prediction tasks.
What's missing
The paper does not discuss computational overhead comparisons with other post-hoc stabilization methods beyond generic shift-based TTA, nor does it evaluate performance on datasets beyond Cityscapes or on other dense prediction tasks at scale. The generalizability of the K=4 optimal configuration across different ViT architectures and image resolutions remains unclear.
What different sources said
- arXiv cs.LGCenter
Phase Marginalization for Patch-Grid Instability in Vision Transformers
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