Pengfei Xiong

Computer Vision and Pattern Recognition · 2018–2022

A researcher in the Science corpus: 4 papers; trusts 690 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 131 citations into it; #9,955 of 21,575 by trust here, #6,954 by citations
• Artificial Intelligence — 54 citations into it; #21,626 of 35,345 by trust here, #14,718 by citations
• Multimodal Learning — 22 citations into it
• Model Architectures — 20 citations into it
• Evaluation & Benchmarks — 16 citations into it
• Aerospace Engineering — 10 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Natural Language Processing — 7 citations into it

Whom Pengfei Xiong 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. Yoshua Bengio
7. Yann LeCun
8. Liang-Chieh Chen
9. Ilya Sutskever
10. Karen Simonyan

Who trusts Pengfei Xiong overall

1. Yimian Dai
2. Jiacong Xu
3. Yuval Nirkin
4. Yiquan Wu
5. Huihui Pan
6. Changqian Yu
7. F. Sultana
8. Hanchao Li
9. Andrew Tao
10. Golnaz Ghiasi

Papers from Pengfei Xiong's perspective

Ordered by how strongly the researchers Pengfei Xiong 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

• Pyramid Attention Network for Semantic Segmentation (2018) — 1,011 citations
• CLIP2Video: Mastering Video-Text Retrieval via Image CLIP (2021) — 366 citations
• DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation (2019) — 676 citations
• Practical Stereo Matching via Cascaded Recurrent Network with Adaptive Correlation (2022) — 400 citations