Hedi Tabia

Computer Vision and Pattern Recognition · 2017–2022

A researcher in the Science corpus: 4 papers; trusts 839 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 194 citations into it; #8,913 of 21,575 by trust here, #10,334 by citations
• Generative Models — 52 citations into it
• Human-Computer Interaction — 48 citations into it
• Artificial Intelligence — 40 citations into it; #15,367 of 35,345 by trust here, #16,471 by citations
• Biomedical Engineering — 33 citations into it
• 3D Vision & Pose — 20 citations into it; #407 of 689 by trust here, #529 by citations
• Model Architectures — 11 citations into it
• Evaluation & Benchmarks — 10 citations into it

Whom Hedi Tabia trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kaiming He
2. Christian Szegedy
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. Diederik P. Kingma
7. Yoshua Bengio
8. Andrew Zisserman
9. L. Eon Bottou
10. Ross B. Girshick

Who trusts Hedi Tabia overall

1. Diogo Carbonera Luvizon
2. Jiefeng Li
3. Ce Zheng
4. Yucheng Chen
5. Ye Yuan
6. Haoshu Fang

Papers from Hedi Tabia's perspective

Ordered by how strongly the researchers Hedi Tabia trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• 2D/3D Pose Estimation and Action Recognition Using Multitask Deep Learning (2018) — 535 citations
• Human Pose Regression by Combining Indirect Part Detection and Contextual Information (2017) — 268 citations
• Learning features combination for human action recognition from skeleton sequences (2017) — 108 citations
• Generative Adversarial Networks for Face Generation: A Survey (2022) — 277 citations