Papers › VₖD: Improving Knowledge Distillation using Orthogonal Projections
VₖD: Improving Knowledge Distillation using Orthogonal Projections
Roy Miles, Ismail Elezi, Jiankang Deng
Knowledge distillation is an effective method for training small and efficient deep learning models. However, the efficacy of a single method can degenerate when transferring to other tasks, modalities, or even other architectures. To address this limitation, we propose a novel constrained feature distillation method. This method is derived from a small set of core principles, which results in two emerging components: an orthogonal projection and a task-specific normalisation. Equipped with both of these components, our transformer models can outperform all previous methods on ImageNet and reach up to a 4.4% relative improvement over the previous state-of-the-art methods. To further demonstrate the generality of our method, we apply it to object detection and image generation, whereby we obtain consistent and substantial performance improvements over state-of-the-art. Code and models are publicly available: https://github.com/roymiles/vkd
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Code
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Code Syntology ran Syntology
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Knowledge Distillation | ImageNet | VkD (T:RegNety 160 S:DeiT-S) | CRD training setting | ✘ | #6 of 52 | Archive leaderboard | report |
| Knowledge Distillation | ImageNet | VkD (T:RegNety 160 S:DeiT-S) | Top-1 accuracy % | 82.9 | #6 of 52 | Archive leaderboard | report |
| Knowledge Distillation | ImageNet | VkD (T:RegNety 160 S:DeiT-S) | model size | 22M | #6 of 52 | Archive leaderboard | report |
| Knowledge Distillation | ImageNet | VkD (T:RegNety 160 S:DeiT-Ti) | CRD training setting | ✘ | #15 of 52 | Archive leaderboard | report |
| Knowledge Distillation | ImageNet | VkD (T:RegNety 160 S:DeiT-Ti) | Top-1 accuracy % | 79.2 | #15 of 52 | Archive leaderboard | report |
| Knowledge Distillation | ImageNet | VkD (T:RegNety 160 S:DeiT-Ti) | model size | 6M | #15 of 52 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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