Xiantong Zhen

Computer Vision and Pattern Recognition · 2014–2023

A researcher in the Science corpus: 7 papers; trusts 669 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 304 citations into it; #21,059 of 21,575 by trust here, #10,677 by citations
• Artificial Intelligence — 158 citations into it; #26,930 of 35,345 by trust here, #13,760 by citations
• Generative Models — 39 citations into it
• Meta & Continual Learning — 37 citations into it; #937 of 1,041 by trust here, #782 by citations
• Representation & Self-Supervised Learning — 37 citations into it
• Model Architectures — 31 citations into it
• Probabilistic & Bayesian Methods — 20 citations into it
• Statistical Learning Theory — 14 citations into it

Whom Xiantong Zhen trusts overall

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

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

Who trusts Xiantong Zhen overall

1. Jorge Armando Mendez Mendez
2. Mengyang Yu
3. Samitha Herath
4. Haoxuan Qu
5. Matteo Boschini

Papers from Xiantong Zhen's perspective

Ordered by how strongly the researchers Xiantong Zhen 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. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Few-Shot Semantic Segmentation with Democratic Attention Networks (2020) — 234 citations
• Spatio-Temporal Laplacian Pyramid Coding for Action Recognition (2014) — 237 citations
• Implicit Diffusion Models for Continuous Super-Resolution (2023) — 383 citations
• Deep 3D human pose estimation: A review (2021) — 392 citations
• Kernel Continual Learning (2021) — 48 citations
• Learning to Learn Kernels with Variational Random Features (2020) — 38 citations
• Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks (2019) — 354 citations