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Mubarak Shah

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
ORCID 0000-0001-6172-5572
same name
  • Mubarak Shah — 15 papers, h 6
  • Mubarak Shah — 15 papers, h 7
  • Mubarak Shah — 13 papers, h 9
  • Mubarak Shah — 11 papers, h 5
  • Mubarak Shah — 11 papers, h 3
  • Mubarak Shah — 9 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162021
most citedVideo Description: A Survey of Methods, Datasets and Evaluation Metrics

153 citations · 162 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2021★ 1 cited

Routing with Self-Attention for Multimodal Capsule Networks

Kevin Duarte, Brian Chen, Nina Shvetsova +7

The task of multimodal learning has seen a growing interest recently as it allows for training neural architectures based on different modalities such as vision, text, and audio. O…

cs.CV2018★ 153 cited

Video Description: A Survey of Methods, Datasets and Evaluation Metrics

Nayyer Aafaq, Ajmal Mian, Wei Liu +2

Video description is the automatic generation of natural language sentences that describe the contents of a given video. It has applications in human-robot interaction, helping the…

cs.CV2017★ 4 cited

Large-scale Image Geo-Localization Using Dominant Sets

Eyasu Zemene, Yonatan Tariku, Haroon Idrees +3

This paper presents a new approach for the challenging problem of geo-locating an image using image matching in a structured database of city-wide reference images with known GPS c…

cs.CV2016★ 4 cited

Re-identification of Humans in Crowds using Personal, Social and Environmental Constraints

Shayan Modiri Assari, Haroon Idrees, Mubarak Shah

This paper addresses the problem of human re-identification across non-overlapping cameras in crowds.Re-identification in crowded scenes is a challenging problem due to large numbe…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.