Prompt Guided Transformer for Multi-Task Dense Prediction
Author:
Affiliation:
1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
2. School of Information Science and Technology, Chuxiong Normal University, Chuxiong, China
Funder
National Natural Science Foundation of China
Shanghai Municipal Science and Technology Major Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/6046/10384483/10380775.pdf?arnumber=10380775
Reference83 articles.
1. Exploring visual prompts for adapting large-scale models;Bahng,2022
2. Stochastic Filter Groups for Multi-Task CNNs: Learning Specialist and Generalist Convolution Kernels
3. Automated search for resource-efficient branched multi-task networks;Brggemann,2020
4. Exploring Relational Context for Multi-Task Dense Prediction
5. End-to-End Object Detection with Transformers
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