Lei Zhou

Computer Vision and Pattern Recognition · 2018–2022

A researcher in the Science corpus: 7 papers; trusts 358 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 176 citations into it; #17,941 of 21,575 by trust here, #8,502 by citations
• Aerospace Engineering — 116 citations into it
• Geology — 45 citations into it
• Artificial Intelligence — 42 citations into it
• Computational Mechanics — 33 citations into it
• Graph Learning — 27 citations into it
• 3D Vision & Pose — 21 citations into it
• Representation & Self-Supervised Learning — 12 citations into it

Whom Lei Zhou trusts overall

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

1. David G. Lowe
2. Kaiming He
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Andrew Zisserman
6. Karen Simonyan
7. Alex Krizhevsky
8. Christopher Bongsoo Choy
9. Yann LeCun
10. Yoshua Bengio

Who trusts Lei Zhou overall

1. Vincent Leroy
2. Shikhar Vashishth
3. Zixin Luo
4. Zheng Qin
5. Jiayi Ma
6. Hongkai Chen

Papers from Lei Zhou's perspective

Ordered by how strongly the researchers Lei Zhou 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• BlendedMVS: A Large-Scale Dataset for Generalized Multi-View Stereo Networks (2019) — 756 citations
• Learning Two-View Correspondences and Geometry Using Order-Aware Network (2019) — 368 citations
• ASpanFormer: Detector-Free Image Matching with Adaptive Span Transformer (2022) — 301 citations
• PointDSC: Robust Point Cloud Registration using Deep Spatial Consistency (2021) — 370 citations
• D3Feat: Joint Learning of Dense Detection and Description of 3D Local Features (2020) — 531 citations
• ASLFeat: Learning Local Features of Accurate Shape and Localization (2020) — 358 citations
• End-to-End Structure-Aware Convolutional Networks for Knowledge Base Completion (2018) — 732 citations