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researcher

M. Hosseinzadeh

4 papers hereh-index 8433 citations21 works total

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

author position
  • middle author3

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

fields
  • cs.CV3
  • cs.LG1
same name
  • M. Hosseinzadeh — 11 papers, h 25
  • M. Hosseinzadeh — 5 papers, h 11
  • M. Hosseinzadeh — 3 papers
  • M. Hosseinzadeh — 2 papers
  • M. Hosseinzadeh — 1 paper, h 14

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
20192022
most citedCrowd Counting Using Scale-Aware Attention Networks

9 citations · 12 across the 3 of their papers we have counts for

collaborators

4 papers

cs.LG2022★ 1 cited

Few-Shot Learning of Compact Models via Task-Specific Meta Distillation

Yong Wu, Shekhor Chanda, Mehrdad Hosseinzadeh +2

We consider a new problem of few-shot learning of compact models. Meta-learning is a popular approach for few-shot learning. Previous work in meta-learning typically assumes that t…

cs.CV2020★ 2 cited

Unsupervised Learning of Camera Pose with Compositional Re-estimation

Seyed Shahabeddin Nabavi, Mehrdad Hosseinzadeh, Ramin Fahimi +1

We consider the problem of unsupervised camera pose estimation. Given an input video sequence, our goal is to estimate the camera pose (i.e. the camera motion) between consecutive…

cs.CV2019

Towards Shape Biased Unsupervised Representation Learning for Domain Generalization

Nader Asadi, Amir M. Sarfi, Mehrdad Hosseinzadeh +2

It is known that, without awareness of the process, our brain appears to focus on the general shape of objects rather than superficial statistics of context. On the other hand, lea…

cs.CV2019★ 9 cited

Crowd Counting Using Scale-Aware Attention Networks

Mohammad Asiful Hossain, Mehrdad Hosseinzadeh, Omit Chanda +1

In this paper, we consider the problem of crowd counting in images. Given an image of a crowded scene, our goal is to estimate the density map of this image, where each pixel value…

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