Zhenan Sun

Computer Vision and Pattern Recognition · 2005–2021

A researcher in the Science corpus: 18 papers; trusts 1,898 researchers and is trusted by 28 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 704 citations into it; #5,984 of 21,575 by trust here, #4,212 by citations
• Generative Models — 289 citations into it
• Artificial Intelligence — 279 citations into it; #20,388 of 35,345 by trust here, #27,551 by citations
• Signal Processing — 118 citations into it; #2,114 of 7,572 by trust here, #1,485 by citations
• Computational Mechanics — 87 citations into it
• Representation & Self-Supervised Learning — 81 citations into it
• Media Technology — 45 citations into it
• Optimization & Training — 41 citations into it

Whom Zhenan Sun trusts overall

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

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

Who trusts Zhenan Sun overall

1. Tien-Ping Tan
2. J. Unar
3. Shiv Ram Dubey
4. Jian Liang
5. Woo Chaw Seng
6. Adrian Bulat
7. Xiang Wu
8. Shiyu Chang
9. Zhaofeng He
10. Ran He

Papers from Zhenan Sun's perspective

Ordered by how strongly the researchers Zhenan Sun 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. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. GENERATIVE ADVERSARIAL NETS

Their papers

• IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis (2018) — 299 citations
• A Light CNN for Deep Face Representation With Noisy Labels (2015) — 1,144 citations
• Wavelet-SRNet: A Wavelet-Based CNN for Multi-scale Face Super Resolution (2017) — 520 citations
• PyMAF: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop (2021) — 393 citations
• Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-free Approach (2018) — 326 citations
• Toward Accurate and Fast Iris Segmentation for Iris Biometrics (2009) — 443 citations
• Half-Quadratic-Based Iterative Minimization for Robust Sparse Representation (2014) — 327 citations
• One Shot Face Swapping on Megapixels (2021) — 205 citations
• Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators? (2020) — 20 citations
• Learning an Evolutionary Embedding via Massive Knowledge Distillation (2020) — 35 citations
• A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications (2020) — 1,136 citations
• Distant Supervised Centroid Shift: A Simple and Efficient Approach to Visual Domain Adaptation (2019) — 92 citations
• Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition (2017) — 297 citations
• Feature Selection Based on Structured Sparsity: A Comprehensive Study (2017) — 250 citations
• Deep Supervised Discrete Hashing (2017) — 334 citations
• Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition (2010) — 307 citations
• Ordinal Measures for Iris Recognition (2009) — 325 citations
• Ordinal palmprint represention for personal identification [represention read representation] (2005) — 491 citations