Xun Huang

Computer Vision and Pattern Recognition · with Liu · 2015–2022

A researcher in the Science corpus: 9 papers; trusts 1,202 researchers and is trusted by 2,846 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 371 citations into it; #707 of 21,575 by trust here, #918 by citations
• Generative Models — 230 citations into it; #899 of 1,956 by trust here, #297 by citations
• Artificial Intelligence — 147 citations into it
• Computer Graphics and Computer-Aided Design — 73 citations into it; #1,436 of 1,584 by trust here, #215 by citations
• Computational Mechanics — 45 citations into it; #9,019 of 10,001 by trust here, #903 by citations
• Representation & Self-Supervised Learning — 31 citations into it
• Model Architectures — 29 citations into it
• Probabilistic & Bayesian Methods — 29 citations into it

Whom Xun Huang trusts overall

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

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

Who trusts Xun Huang overall

1. Ming-Yu Liu
2. Jun-Yan Zhu
3. Taesung Park
4. Wenguan Wang
5. Richard Zhang
6. Tero Karras
7. Yijun Li
8. Aviv Gabbay
9. Weihao Xia
10. Rameen Abdal

Papers from Xun Huang's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
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

• Arbitrary Style Transfer in Real-Time with Adaptive Instance Normalization (2017) — 5,355 citations
• Multimodal Unsupervised Image-to-Image Translation (2018) — 2,739 citations
• eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers (2022) — 1,087 citations
• Stacked Generative Adversarial Networks (2016) — 470 citations
• Few-Shot Unsupervised Image-to-Image Translation (2019) — 679 citations
• Magic3D: High-Resolution Text-to-3D Content Creation (2022) — 1,645 citations
• SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks (2015) — 605 citations
• Top-Down Learning for Structured Labeling with Convolutional Pseudoprior (2015) — 39 citations
• PointFlow: 3D Point Cloud Generation With Continuous Normalizing Flows (2019) — 831 citations