Hossein Rahmani
Computer Vision and Pattern Recognition · 2014–2021
A researcher in the Science corpus: 13 papers; trusts 2,225 researchers and is trusted by 77 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 895 citations into it; #3,189 of 21,575 by trust here, #3,404 by citations
- Artificial Intelligence — 551 citations into it; #6,009 of 35,345 by trust here, #8,619 by citations
- Biomedical Engineering — 213 citations into it; #593 of 10,734 by trust here, #2,604 by citations
- Meta & Continual Learning — 173 citations into it; #585 of 1,041 by trust here, #583 by citations
- Human-Computer Interaction — 124 citations into it; #603 of 2,253 by trust here, #495 by citations
- Representation & Self-Supervised Learning — 87 citations into it; #1,829 of 3,145 by trust here, #1,885 by citations
- Model Architectures — 77 citations into it
- 3D Vision & Pose — 66 citations into it; #190 of 689 by trust here, #362 by citations
Whom Hossein Rahmani trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Karen Simonyan
- Kaiming He
- Ross B. Girshick
- Xiaodong Yang
- Diederik P. Kingma
- Andrew Zisserman
- Yann LeCun
Who trusts Hossein Rahmani overall
- Amir Shahroudy
- Ajmal Saeed Mian
- Jun Liu
- Zehua Sun
- Seungryul Baek
- Tian-Tsong Ng
- Qiuhong Ke
- Mohammed Bennamoun
- G. Wang
- Pichao Wang
Papers from Hossein Rahmani's perspective
Ordered by how strongly the researchers Hossein Rahmani trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- 3D Action Recognition from Novel Viewpoints (2016) — 202 citations
- Learning a non-linear knowledge transfer model for cross-view action recognition (2015) — 155 citations
- Histogram of Oriented Principal Components for Cross-View Action Recognition (2014) — 194 citations
- A Guide to Convolutional Neural Networks for Computer Vision (2018) — 617 citations
- HOPC: Histogram of Oriented Principal Components of 3D Pointclouds for Action Recognition (2014) — 194 citations
- Learning Action Recognition Model from Depth and Skeleton Videos (2017) — 109 citations
- Real time action recognition using histograms of depth gradients and random decision forests (2014) — 116 citations
- Global Regularizer and Temporal-Aware Cross-Entropy for Skeleton-Based Early Action Recognition (2018) — 14 citations
- Else-Net: Elastic Semantic Network for Continual Action Recognition from Skeleton Data (2021) — 47 citations
- Recent Advances of Continual Learning in Computer Vision: An Overview (2021) — 114 citations
- Human Action Recognition From Various Data Modalities: A Review (2020) — 800 citations
- Learning a Deep Model for Human Action Recognition from Novel Viewpoints (2016) — 220 citations
- Action Classification with Locality-Constrained Linear Coding (2014) — 25 citations