Canonical logit- and feature-based knowledge distillation outperform complex segmentation-specific methods under matched wall-clock compute and achieve near-teacher performance with extended training on Cityscapes and ADE20K.
Structured knowledge distillation for semantic segmentation
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The Surprising Effectiveness of Canonical Knowledge Distillation for Semantic Segmentation
Canonical logit- and feature-based knowledge distillation outperform complex segmentation-specific methods under matched wall-clock compute and achieve near-teacher performance with extended training on Cityscapes and ADE20K.