Sangmin Oh

Computer Vision and Pattern Recognition · 2011–2013

A researcher in the Science corpus: 2 papers; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 11 citations into it

Whom Sangmin Oh trusts overall

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

1. Li Fei-Fei
2. Andrew Zisserman
3. Ross B. Girshick
4. Andrea Vedaldi
5. Antonio Torralba
6. Deva Ramanan
7. Mubarak Shah
8. Pedro F. Felzenszwalb
9. Jitendra Malik
10. David G. Lowe

Who trusts Sangmin Oh overall

1. Jacob Walker

Papers from Sangmin Oh's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Object Detection with Discriminatively Trained Part Based Models
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet Large Scale Visual Recognition Challenge
9. Going deeper with convolutions
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• AVSS 2011 demo session: A large-scale benchmark dataset for event recognition in surveillance video (2011) — 435 citations
• Compositional Models for Video Event Detection: A Multiple Kernel Learning Latent Variable Approach (2013) — 62 citations