Yupan Huang

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 4 papers; trusts 596 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 150 citations into it; #15,795 of 21,575 by trust here, #8,021 by citations
• Artificial Intelligence — 123 citations into it; #25,741 of 35,345 by trust here, #12,244 by citations
• Multimodal Learning — 84 citations into it; #843 of 1,211 by trust here, #702 by citations
• Natural Language Processing — 38 citations into it
• Model Architectures — 25 citations into it
• Generative Models — 21 citations into it
• Evaluation & Benchmarks — 20 citations into it
• Representation & Self-Supervised Learning — 18 citations into it

Whom Yupan Huang trusts overall

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

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

Who trusts Yupan Huang overall

1. Hongwei Xue
2. Zi-Yi Dou
3. Zhe Gan
4. Yixuan Su
5. Jianfeng Wang
6. Kenton C. T. Lee
7. Xiao Wang
8. P. Xu

Papers from Yupan Huang's perspective

Ordered by how strongly the researchers Yupan Huang 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning (2021) — 313 citations
• Probing Inter-modality: Visual Parsing with Self-Attention for Vision-Language Pre-training (2021) — 100 citations
• LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking (2022) — 833 citations
• Unifying Multimodal Transformer for Bi-directional Image and Text Generation (2021) — 67 citations