Generative Denoise Distillation: Simple stochastic noises induce efficient knowledge transfer for dense prediction-Reference-Cited by-同舟云学术

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Generative Denoise Distillation: Simple stochastic noises induce efficient knowledge transfer for dense prediction

Published:2024-10 Issue: Volume:302 Page:112365
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Liu Zhaoge^ORCID,Xu Xiaohao,Cao Yunkang^ORCID,Shen Weiming^ORCID

Funder

Ministry of Industry and Information Technology of the People's Republic of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Reference47 articles.

1. Learning transferable visual models from natural language supervision;Radford,2021

2. Segment anything;Kirillov,2023

3. The dawn of lmms: Preliminary explorations with gpt-4v (ision);Yang,2023

4. Towards generic anomaly detection and understanding: Large-scale visual-linguistic model (GPT-4V) takes the lead;Cao,2023

5. Vision transformers for dense prediction;Ranftl,2021

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