Chenxu Luo
Computer Vision and Pattern Recognition · 2018–2019
A researcher in the Science corpus: 2 papers; trusts 695 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 97 citations into it; #14,036 of 21,575 by trust here, #14,151 by citations
- Artificial Intelligence — 22 citations into it
- Aerospace Engineering — 16 citations into it
- Evaluation & Benchmarks — 10 citations into it
- Model Architectures — 10 citations into it
Whom Chenxu Luo trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Karen Simonyan
- Ross B. Girshick
- Geoffrey E. Hinton
- Alex Krizhevsky
- Diederik P. Kingma
- Andrew Zisserman
- Yann LeCun
- Yoshua Bengio
- Ilya Sutskever
Who trusts Chenxu Luo overall
- Kunchang Li
- Max Bain
- Clément Godard
- Jamie Watson
- Marvin Klingner
- Yali Wang
- Arsha Nagrani
- Gabriel J. Brostow
- Oisin Mac Aodha
- Yin Li
Papers from Chenxu Luo's perspective
Ordered by how strongly the researchers Chenxu Luo 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Grouped Spatial-Temporal Aggregation for Efficient Action Recognition (2019) — 172 citations
- Every Pixel Counts ++: Joint Learning of Geometry and Motion with 3D Holistic Understanding (2018) — 313 citations