# Structural Knowledge Distillation for Object Detection Source: [Structural Knowledge Distillation for Object Detection]() Collection index: [llms.txt]() Data updated: 2026-01-04T05:22:49.561Z Authors: Philip de Rijk, Lukas Schneider, Marius Cordts, Dariu M. Gavrila Published: 2022-11-23T17:06:52.000Z ## Abstract Knowledge Distillation (KD) is a well-known training paradigm in deep neural networks where knowledge acquired by a large teacher model is transferred to a small student. KD has proven to be an effective technique to significantly improve the student's performance for various tasks including object detection. As such, KD techniques mostly rely on guidance at the intermediate feature level, which is typically implemented by minimizing an lp-norm distance between teacher and student activations during training. In this paper, we propose a replacement for the pixel-wise independent lp-norm based on the structural similarity (SSIM). By taking into account additional contrast and structural cues, feature importance, correlation and spatial dependence in the feature space are considered in the loss formulation. Extensive experiments on MSCOCO demonstrate the effectiveness of our method across different training schemes and architectures. Our method adds only little computational overhead, is straightforward to implement and at the same time it significantly outperforms the standard lp-norms. Moreover, more complex state-of-the-art KD methods using attention-based sampling mechanisms are outperformed, including a +3.5 AP gain using a Faster R-CNN R-50 compared to a vanilla model. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Object Detection on COCO (minival)](): Object Detection; COCO (minival); mAP: 42.3. - [Object Detection on MS-COCO 2017 (val)](): Object Detection; MS-COCO 2017 (val); mAP: not recorded. ## Original sources and implementation [Original paper]() [PDF]()