Changxing Ding

Computer Vision and Pattern Recognition · 2014–2020

A researcher in the Science corpus: 8 papers; trusts 1,282 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 267 citations into it; #5,798 of 21,575 by trust here, #7,938 by citations
• Artificial Intelligence — 52 citations into it
• Signal Processing — 44 citations into it; #1,433 of 7,572 by trust here, #2,276 by citations
• Model Architectures — 24 citations into it
• Media Technology — 18 citations into it
• Biomedical Engineering — 16 citations into it
• Generative Models — 16 citations into it
• Representation & Self-Supervised Learning — 16 citations into it

Whom Changxing Ding trusts overall

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

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

Who trusts Changxing Ding overall

1. Mei Wang
2. Dacheng Tao
3. Xi Yin
4. Dhanesh Ramachandram
5. Weihong Deng
6. Yongming Rao
7. Xijun Wang
8. Yoanna Martínez-Díaz
9. R. Liu
10. Xiaoming Liu

Papers from Changxing Ding's perspective

Ordered by how strongly the researchers Changxing Ding 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. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A Comprehensive Survey on Pose-Invariant Face Recognition (2015) — 329 citations
• Robust Face Recognition via Multimodal Deep Face Representation (2015) — 414 citations
• Trunk-Branch Ensemble Convolutional Neural Networks for Video-Based Face Recognition (2016) — 406 citations
• Multi-Directional Multi-Level Dual-Cross Patterns for Robust Face Recognition (2014) — 360 citations
• GPS-Net: Graph Property Sensing Network for Scene Graph Generation (2020) — 338 citations
• Learning Oracle Attention for High-Fidelity Face Completion (2020) — 46 citations
• Batch Coherence-Driven Network for Part-Aware Person Re-Identification (2020) — 25 citations
• Two-Stage Cascaded U-Net: 1st Place Solution to BraTS Challenge 2019 Segmentation Task (2019) — 337 citations