Sifei Liu

Computer Vision and Pattern Recognition · with Yang · 2012–2023

A researcher in the Science corpus: 9 papers; trusts 1,235 researchers and is trusted by 85 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 343 citations into it; #3,471 of 21,575 by trust here, #3,017 by citations
• Artificial Intelligence — 139 citations into it
• Generative Models — 55 citations into it; #1,014 of 1,956 by trust here, #878 by citations
• Model Architectures — 53 citations into it
• Media Technology — 36 citations into it; #2,872 of 3,621 by trust here, #1,329 by citations
• Computational Mechanics — 25 citations into it
• Evaluation & Benchmarks — 24 citations into it
• Computer Graphics and Computer-Aided Design — 22 citations into it

Whom Sifei Liu trusts overall

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

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

Who trusts Sifei Liu overall

1. Xinjing Cheng
2. Jinsun Park
3. X. Wang
4. Ming-Hsuan Yang
5. Jiawei Zhang
6. Xiangtai Li
7. Peng Wang
8. Jianwei Yang
9. Yijun Li
10. Michael Gharbi

Papers from Sifei Liu's perspective

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

Their papers

• GroupViT: Semantic Segmentation Emerges from Text Supervision (2022) — 748 citations
• Generative Face Completion (2017) — 631 citations
• Learning Affinity via Spatial Propagation Networks (2017) — 318 citations
• Learning Continuous Image Representation with Local Implicit Image Function (2020) — 970 citations
• Learning Recursive Filters for Low-Level Vision via a Hybrid Neural Network (2016) — 168 citations
• Multi-objective convolutional learning for face labeling (2015) — 139 citations
• Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models (2023) — 479 citations
• A face antispoofing database with diverse attacks (2012) — 870 citations
• Low-Light Image Enhancement via a Deep Hybrid Network (2019) — 460 citations