Liangchen Song

Computer Vision and Pattern Recognition · 2018–2021

A researcher in the Science corpus: 3 papers; trusts 320 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 103 citations into it
• Artificial Intelligence — 42 citations into it
• Model Architectures — 10 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Optimization & Training — 8 citations into it

Whom Liangchen Song trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Shaoqing Ren
4. Geoffrey E. Hinton
5. Alex Krizhevsky
6. Yann LeCun
7. Yoshua Bengio
8. Diederik P. Kingma
9. X. Zhang
10. Karen Simonyan

Who trusts Liangchen Song overall

1. Yixiao Ge
2. Xin Jin
3. Kecheng Zheng
4. Dapeng Chen

Papers from Liangchen Song's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
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

• Track to Detect and Segment: An Online Multi-Object Tracker (2021) — 417 citations
• Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (2020) — 79 citations
• Unsupervised Domain Adaptive Re-Identification: Theory and Practice (2018) — 363 citations