Peike Li

Computer Vision and Pattern Recognition · 2019–2023

A researcher in the Science corpus: 4 papers; trusts 545 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 88 citations into it; #13,599 of 21,575 by trust here, #12,172 by citations
• Artificial Intelligence — 54 citations into it
• Signal Processing — 25 citations into it
• Generative Models — 19 citations into it
• Optimization & Training — 11 citations into it
• Representation & Self-Supervised Learning — 9 citations into it; #2,197 of 3,145 by trust here, #2,558 by citations
• Model Architectures — 8 citations into it
• Radiology, Nuclear Medicine and Imaging — 6 citations into it

Whom Peike Li trusts overall

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

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

Who trusts Peike Li overall

1. Golnaz Ghiasi
2. Oran Gafni
3. Xiuye Gu
4. Mengde Xu
5. Kuan Zhu
6. Chong Zhou
7. Yin Cui
8. Oron Ashual
9. Tsung-Yi Lin
10. Zheng Zhang

Papers from Peike Li's perspective

Ordered by how strongly the researchers Peike Li 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. ImageNet: A large-scale hierarchical image database
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

• Consistent Structural Relation Learning for Zero-Shot Segmentation (2020) — 88 citations
• Dual Embedding Learning for Video Instance Segmentation (2019) — 21 citations
• Self-Correction for Human Parsing (2019) — 445 citations
• JEN-1: Text-Guided Universal Music Generation with Omnidirectional Diffusion Models (2023) — 59 citations