Alex ChiChung Kot

Computer Vision and Pattern Recognition · 2002–2023

A researcher in the Science corpus: 14 papers; trusts 1,552 researchers and is trusted by 40 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 696 citations into it; #4,390 of 21,575 by trust here, #2,983 by citations
• Artificial Intelligence — 340 citations into it; #6,968 of 35,345 by trust here, #5,749 by citations
• Biomedical Engineering — 191 citations into it; #2,747 of 10,734 by trust here, #2,323 by citations
• Human-Computer Interaction — 141 citations into it; #2,124 of 2,253 by trust here, #1,041 by citations
• 3D Vision & Pose — 83 citations into it; #497 of 689 by trust here, #548 by citations
• Model Architectures — 78 citations into it; #1,040 of 2,278 by trust here, #1,038 by citations
• Representation & Self-Supervised Learning — 66 citations into it; #1,437 of 3,145 by trust here, #1,370 by citations
• Evaluation & Benchmarks — 43 citations into it

Whom Alex ChiChung Kot trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Alex Krizhevsky
4. Yoshua Bengio
5. Ross B. Girshick
6. Yann LeCun
7. Diederik P. Kingma
8. Karen Simonyan
9. Alex Graves
10. Ilya Sutskever

Who trusts Alex ChiChung Kot overall

1. Jun Liu
2. Kaiyang Zhou
3. Amir Shahroudy
4. Yusuke Iwasawa
5. Divyat Mahajan
6. G. Wang
7. Anmin Zou
8. Zehua Sun
9. Fabio Maria Carlucci
10. Qiuhong Ke

Papers from Alex ChiChung Kot's perspective

Ordered by how strongly the researchers Alex ChiChung Kot 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. Long Short-Term Memory
5. ImageNet: A large-scale hierarchical image database
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Domain Generalization with Adversarial Feature Learning (2018) — 1,510 citations
• NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding (2019) — 1,730 citations
• Heterogeneous Domain Generalization Via Domain Mixup (2020) — 173 citations
• Dual Attention Matching Network for Context-Aware Feature Sequence Based Person Re-identification (2018) — 486 citations
• Feature Boosting Network For 3D Pose Estimation (2019) — 129 citations
• Low-Light Image Enhancement with Normalizing Flow (2021) — 590 citations
• Global Context-Aware Attention LSTM Networks for 3D Action Recognition (2017) — 655 citations
• Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates (2017) — 504 citations
• SinSR: Diffusion-Based Image Super-Resolution in a Single Step (2023) — 337 citations
• Skeleton-Based Online Action Prediction Using Scale Selection Network (2019) — 151 citations
• SSNet: Scale Selection Network for Online 3D Action Prediction (2018) — 55 citations
• Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks (2017) — 539 citations
• Eigenfeature Regularization and Extraction in Face Recognition (2008) — 328 citations
• Nonlinear dynamic system identification using Chebyshev functional link artificial neural networks (2002) — 342 citations