Christian Wojek
Computer Vision and Pattern Recognition · 2008–2014
A researcher in the Science corpus: 8 papers; trusts 734 researchers and is trusted by 3,312 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 190 citations into it; #627 of 21,575 by trust here, #1,530 by citations
- Artificial Intelligence — 53 citations into it; #4,091 of 35,345 by trust here, #5,120 by citations
- Automotive Engineering — 20 citations into it; #2,681 of 3,081 by trust here, #1,313 by citations
- Aerospace Engineering — 19 citations into it; #844 of 6,421 by trust here, #3,175 by citations
- Evaluation & Benchmarks — 19 citations into it; #961 of 3,147 by trust here, #1,071 by citations
- Media Technology — 15 citations into it
- Ocean Engineering — 11 citations into it
- Environmental Engineering — 10 citations into it; #4,909 of 5,479 by trust here, #1,728 by citations
Whom Christian Wojek trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Navneet Dalal
- Antonio Torralba
- David G. Lowe
- Paul A. Viola
- Dariu M. Gavrila
- Geoffrey E. Hinton
- Bill Triggs
- Pedro F. Felzenszwalb
- Dorin Comaniciu
- Alex Krizhevsky
Who trusts Christian Wojek overall
- Piotr Doll'ar
- Wanli Ouyang
- Xiaogang Wang
- Bernt Schiele
- Andreas Geiger
- Anurag Arnab
- Rodrigo Benenson
- Anelia Angelova
- Shanshan Zhang
- Xiaodan Liang
Papers from Christian Wojek's perspective
Ordered by how strongly the researchers Christian Wojek trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- 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
- Pedestrian detection: A benchmark (2009) — 1,503 citations
- Pedestrian Detection: An Evaluation of the State of the Art (2012) — 3,350 citations
- Multi-cue onboard pedestrian detection (2009) — 440 citations
- 3D Traffic Scene Understanding From Movable Platforms (2014) — 417 citations
- A Dynamic Conditional Random Field Model for Joint Labeling of Object and Scene Classes (2008) — 141 citations
- Learning people detection models from few training samples (2011) — 92 citations
- Sliding-Windows for Rapid Object Class Localization: A Parallel Technique (2008) — 136 citations
- D Traffic Scene Understanding from Movable Platforms (2013)