AppFuse: An Appearance Fusion Framework for Saliency Cues-Reference-Cited by-同舟云学术

AppFuse: An Appearance Fusion Framework for Saliency Cues

Author:

Jerripothula Koteswar Rao¹^ORCID,Mukherjee Prerana²^ORCID,Cai Jianfei³^ORCID,Lu Shijian⁴^ORCID,Yuan Junsong⁵^ORCID

Affiliation:

1. Computer Science and Engineering Department, Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), New Delhi, India

2. School of Engineering, Jawaharlal Nehru University, New Delhi, India

3. Department of Data Science and AI, Monash University, Clayton, VIC, Australia

4. School of Computer Science and Engineering, Nanyang Technological University, Jurong West, Singapore

5. Computer Science and Engineering Department, State University of New York at Buffalo, Buffalo, NY, USA

Funder

Science and Engineering Research Board (SERB), Department of Science and Technology (DST), Government of India

Infosys Centre for Artificial Intelligence, Indraprastha Institute of Information Technology Delhi

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

Reference75 articles.

2. Semi-supervised domain adaptation for weakly labeled semantic video object segmentation;wang;Proc Asian Conf Comput Vis,2016

3. ICNet: Intra-saliency correlation network for co-saliency detection;jin;Proc Adv Neural Inf Process Syst,2020

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