Wenqi Xian
Computer Vision and Pattern Recognition · 2017–2020
A researcher in the Science corpus: 4 papers; trusts 506 researchers and is trusted by 63 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 150 citations into it; #3,924 of 21,575 by trust here, #2,739 by citations
- Computer Graphics and Computer-Aided Design — 42 citations into it; #1,362 of 1,584 by trust here, #388 by citations
- Generative Models — 28 citations into it
- Artificial Intelligence — 26 citations into it
- Aerospace Engineering — 19 citations into it
- 3D Vision & Pose — 17 citations into it
- Computational Mechanics — 17 citations into it; #8,767 of 10,001 by trust here, #2,509 by citations
- Automotive Engineering — 9 citations into it
Whom Wenqi Xian trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ross B. Girshick
- Yoshua Bengio
- Yann LeCun
- Karen Simonyan
- Fisher Yu
- Ilya Sutskever
Who trusts Wenqi Xian overall
- Sang-Min Park
- Chen Gao
- Keunhong Park
- Guangcong Wang
- Tsu-Jui Fu
- Abdul Jabbar
- Ziyi Yang
- Hang Xu
- Jun-Yan Zhu
- Wei Jiang
Papers from Wenqi Xian's perspective
Ordered by how strongly the researchers Wenqi Xian trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- BDD100K: A Diverse Driving Video Database with Scalable Annotation Tooling (2018) — 960 citations
- BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning (2018) — 3,030 citations
- Space-time Neural Irradiance Fields for Free-Viewpoint Video (2020) — 548 citations
- TextureGAN: Controlling Deep Image Synthesis with Texture Patches (2017) — 300 citations