Song Feng

Computer Vision and Pattern Recognition · with Gunasekara · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 284 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 34 citations into it
• Artificial Intelligence — 24 citations into it
• Natural Language Processing — 17 citations into it
• Generative Models — 14 citations into it
• Multimodal Learning — 13 citations into it
• Evaluation & Benchmarks — 11 citations into it

Whom Song Feng trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Ilya Sutskever
4. Yoshua Bengio
5. Alex Krizhevsky
6. Oriol Vinyals
7. Kaiming He
8. Yann LeCun
9. Jimmy Ba
10. Ross B. Girshick

Who trusts Song Feng overall

1. Jing Yu Koh
2. Hung-Yu Tseng
3. Dong Huk Park
4. Hui Ye
5. Gaurav Mittal

Papers from Song Feng's perspective

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

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

Their papers

• Text2Scene: Generating Compositional Scenes From Textual Descriptions (2018) — 101 citations
• Implicit Discourse Relation Classification: We Need to Talk about Evaluation (2020) — 57 citations