Georg Nebehay

Computer Vision and Pattern Recognition · 2014–2015

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 67 citations into it
• Evaluation & Benchmarks — 15 citations into it

Whom Georg Nebehay trusts

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

1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
2. Jaka Demsar (in Evaluation & Benchmarks)
3. Ross B. Girshick (in Computer Vision and Pattern Recognition)
4. Ming-Hsuan Yang (in Computer Vision and Pattern Recognition)
5. Kaiming He (in Computer Vision and Pattern Recognition)

Papers from Georg Nebehay's perspective

Ordered by how strongly the researchers Georg Nebehay trusts endorse each paper. Same corpus, a different order for every researcher.

1. Unbiased look at dataset bias
2. International Journal of Computer Vision manuscript No. (will be inserted by the editor) The PASCAL Visual Object Classes (VOC) Challenge
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Are we ready for autonomous driving? The KITTI vision benchmark suite
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. The FERET evaluation methodology for face-recognition algorithms

Their papers

• The Visual Object Tracking VOT2014 Challenge Results (2014) — 512 citations
• A Novel Performance Evaluation Methodology for Single-Target Trackers (2015) — 661 citations