Dapeng Chen

Computer Vision and Pattern Recognition · 2016–2021

A researcher in the Science corpus: 10 papers; trusts 1,073 researchers and is trusted by 23 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 367 citations into it; #6,097 of 21,575 by trust here, #3,955 by citations
• Artificial Intelligence — 232 citations into it; #16,792 of 35,345 by trust here, #14,181 by citations
• Representation & Self-Supervised Learning — 96 citations into it
• Meta & Continual Learning — 54 citations into it; #753 of 1,041 by trust here, #692 by citations
• Optimization & Training — 47 citations into it; #1,966 of 2,601 by trust here, #1,986 by citations
• Model Architectures — 32 citations into it
• Evaluation & Benchmarks — 24 citations into it
• Signal Processing — 24 citations into it

Whom Dapeng Chen trusts overall

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

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

Who trusts Dapeng Chen overall

1. Shixiang Tang
2. Liang Zheng
3. Xiatian Zhu
4. Jinguo Zhu
5. Haiyu Zhao
6. Rahul Rama Varior
7. Dangwei Li
8. Zhen Wang
9. Yi Yang
10. Zuozhuo Dai

Papers from Dapeng Chen's perspective

Ordered by how strongly the researchers Dapeng Chen 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. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
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

• The Visual Object Tracking VOT2016 Challenge Results (2016) — 773 citations
• Similarity Learning with Spatial Constraints for Person Re-identification (2016) — 353 citations
• Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID (2020) — 670 citations
• Adapting Object Detectors with Conditional Domain Normalization (2020) — 100 citations
• Layerwise Optimization by Gradient Decomposition for Continual Learning (2021) — 94 citations
• Continual Representation Learning for Biometric Identification (2020) — 50 citations
• Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification (2020) — 663 citations
• Mutual CRF-GNN for Few-shot Learning (2021) — 60 citations
• Complementary Relation Contrastive Distillation (2021) — 101 citations
• Memory-Based Neighbourhood Embedding for Visual Recognition (2019) — 42 citations