UniTR: A Unified TRansformer-Based Framework for Co-Object and Multi-Modal Saliency Detection-Reference-Cited by-同舟云学术

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UniTR: A Unified TRansformer-Based Framework for Co-Object and Multi-Modal Saliency Detection

Published:2024 Issue: Volume:26 Page:7622-7635
ISSN:1520-9210
Container-title:IEEE Transactions on Multimedia
language:
Short-container-title:IEEE Trans. Multimedia

Author:

Guo Ruohao¹^ORCID,Ying Xianghua¹^ORCID,Qi Yanyu²^ORCID,Qu Liao³^ORCID

Affiliation:

1. National Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University, Beijing, China

2. College of Information and Electrical Engineering, China Agricultural University, Beijing, China

3. Electrical and Computer Engineering Department, Carnegie Mellon University, Pittsburgh, PA, USA

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6046/10384483/10444934.pdf?arnumber=10444934

Reference130 articles.

1. Towards Grand Unification of Object Tracking

2. Multi-Task Self-Training for Learning General Representations

3. A Unified Transformer Framework for Group-Based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object Detection

4. Omnivore: A Single Model for Many Visual Modalities

5. Spatiotemporal Saliency Representation Learning for Video Action Recognition

Cited by 1 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. RGB-T Saliency Detection Based on Multiscale Modal Reasoning Interaction;IEEE Transactions on Instrumentation and Measurement;2024

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