Masked Autoencoders Are Stronger Knowledge Distillers-Reference-Cited by-同舟云学术

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Masked Autoencoders Are Stronger Knowledge Distillers

Published:2023-10-01 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
language:
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Author:

Lao Shanshan¹,Song Guanglu²,Liu Boxiao²,Liu Yu²,Yang Yujiu¹

Affiliation:

1. Tsinghua University,Tsinghua Shenzhen International Graduate School

2. Sensetime Research

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377040.pdf?arnumber=10377040

Reference47 articles.

1. Learning efficient object detection models with knowledge distillation;Chen

2. Mmdetection: Open mmlab detection toolbox and benchmark;Chen,2019

3. Rethinking atrous convolution for semantic image segmentation;Chen,2017

4. Distilling Knowledge via Knowledge Review

5. Mmsegmentation: Openmmlab semantic segmentation toolbox and benchmark,2020

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Knowledge in attention assistant for improving generalization in deep teacher–student models;International Journal of Modelling and Simulation;2024-08-22

2. VDKD: A ViT-Based Student-Teacher Knowledge Distillation for Multi-Texture Class Anomaly Detection;2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS);2024-05-17

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