Shaoli Huang

Computer Vision and Pattern Recognition · 2015–2023

A researcher in the Science corpus: 5 papers; trusts 762 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 163 citations into it; #12,536 of 21,575 by trust here, #8,205 by citations
• Artificial Intelligence — 65 citations into it
• Representation & Self-Supervised Learning — 23 citations into it
• Model Architectures — 13 citations into it
• Evaluation & Benchmarks — 12 citations into it
• Developmental Biology — 8 citations into it
• Media Technology — 6 citations into it
• Molecular Biology — 6 citations into it

Whom Shaoli Huang trusts overall

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

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

Who trusts Shaoli Huang overall

1. Xiangteng He
2. Changxing Ding
3. Xiu-Shen Wei
4. Oscar Li
5. Kai Han
6. Hua Zhang
7. Yue Chen
8. Bo Zhao
9. Zhishuai Zhang
10. Yuxin Peng

Papers from Shaoli Huang's perspective

Ordered by how strongly the researchers Shaoli 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. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Part-Stacked CNN for Fine-Grained Visual Categorization (2015) — 464 citations
• Augmenting Strong Supervision Using Web Data for Fine-Grained Categorization (2015) — 85 citations
• Context Refinement for Object Detection (2018) — 105 citations
• Generating Human Motion from Textual Descriptions with Discrete Representations (2023) — 716 citations
• All you need is a good representation: A multi-level and classifier-centric representation for few-shot learning (2019) — 16 citations