Long Chen

Computer Vision and Pattern Recognition · with Liu · 2016–2021

A researcher in the Science corpus: 6 papers; trusts 718 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 188 citations into it; #12,342 of 21,575 by trust here, #3,659 by citations
• Artificial Intelligence — 145 citations into it; #19,799 of 35,345 by trust here, #4,860 by citations
• Model Architectures — 45 citations into it; #2,259 of 2,278 by trust here, #674 by citations
• Natural Language Processing — 34 citations into it
• Multimodal Learning — 33 citations into it
• Optimization & Training — 16 citations into it
• Representation & Self-Supervised Learning — 16 citations into it
• Media Technology — 7 citations into it; #3,241 of 3,621 by trust here, #1,646 by citations

Whom Long Chen trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Karen Simonyan
5. Yoshua Bengio
6. Ilya Sutskever
7. Ross B. Girshick
8. Diederik P. Kingma
9. Yann LeCun
10. Andrew Zisserman

Who trusts Long Chen overall

1. Kun-Juan Wei
2. Ning Xie
3. Hanwang Zhang
4. Md Mostafijur Rahman
5. Jun Xiao
6. Ron Mokady
7. Ting Zhao
8. Jun Shu
9. Meng-Hao Guo
10. Yu-Ying Chou

Papers from Long Chen's perspective

Ordered by how strongly the researchers Long Chen 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
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

• SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning (2016) — 1,836 citations
• Video Question Answering via Attribute-Augmented Attention Network Learning (2017) — 118 citations
• Zero-Shot Visual Recognition Using Semantics-Preserving Adversarial Embedding Networks (2017) — 312 citations
• CrossFormer: A Versatile Vision Transformer Hinging on Cross-scale Attention (2021) — 380 citations
• Counterfactual Samples Synthesizing for Robust Visual Question Answering (2020) — 330 citations
• CrossFormer: A Versatile Vision Transformer Based on Cross-scale Attention (2021) — 72 citations