Pengpeng Liu

Computer Vision and Pattern Recognition · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 355 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 74 citations into it; #18,708 of 21,575 by trust here, #15,529 by citations
• Computational Mechanics — 18 citations into it
• Aerospace Engineering — 15 citations into it
• Computer Graphics and Computer-Aided Design — 13 citations into it
• Artificial Intelligence — 12 citations into it
• Evaluation & Benchmarks — 9 citations into it
• 3D Vision & Pose — 7 citations into it
• Representation & Self-Supervised Learning — 7 citations into it; #2,794 of 3,145 by trust here, #2,957 by citations

Whom Pengpeng Liu trusts overall

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

1. Diederik P. Kingma
2. Thomas Brox
3. Geoffrey E. Hinton
4. Karen Simonyan
5. Alex Krizhevsky
6. Kaiming He
7. Deqing Sun
8. Yann LeCun
9. Jimmy Ba
10. Ross B. Girshick

Who trusts Pengpeng Liu overall

1. Zachary Teed
2. Carl Doersch
3. Jianping Gou
4. Deqing Sun
5. Jia Deng
6. Ankush Gupta
7. Baosheng Yu

Papers from Pengpeng Liu's perspective

Ordered by how strongly the researchers Pengpeng Liu 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. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
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

• SelFlow: Self-Supervised Learning of Optical Flow (2019) — 340 citations
• Function4D: Real-time Human Volumetric Capture from Very Sparse Consumer RGBD Sensors (2021) — 409 citations
• DDFlow: Learning Optical Flow with Unlabeled Data Distillation (2019) — 199 citations