Xing Wei

Computer Vision and Pattern Recognition · with Gong · 2018–2023

A researcher in the Science corpus: 9 papers; trusts 982 researchers and is trusted by 24 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 282 citations into it; #5,344 of 21,575 by trust here, #3,827 by citations
• Artificial Intelligence — 175 citations into it; #7,600 of 35,345 by trust here, #5,682 by citations
• Representation & Self-Supervised Learning — 53 citations into it
• Meta & Continual Learning — 41 citations into it; #235 of 1,041 by trust here, #135 by citations
• Model Architectures — 25 citations into it
• Efficiency & Compression — 22 citations into it
• Radiology, Nuclear Medicine and Imaging — 15 citations into it; #972 of 3,265 by trust here, #1,183 by citations
• Optimization & Training — 14 citations into it

Whom Xing Wei trusts overall

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

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

Who trusts Xing Wei overall

1. Xiaoyu Tao
2. Da-Wei Zhou
3. Xiaopeng Hong
4. Liyuan Wang
5. Tyler L. Hayes
6. Xiu-Shen Wei
7. Xinyuan Chang
8. Han-Jia Ye
9. Songlin Dong
10. Mang Ye

Papers from Xing Wei's perspective

Ordered by how strongly the researchers Xing Wei 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. 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

• Few-Shot Class-Incremental Learning (2020) — 556 citations
• Topology-Preserving Class-Incremental Learning (2020) — 203 citations
• Few-Shot Class-Incremental Learning via Relation Knowledge Distillation (2021) — 224 citations
• Grassmann Pooling as Compact Homogeneous Bilinear Pooling for Fine-Grained Visual Classification (2018) — 86 citations
• Infrared-Visible Cross-Modal Person Re-Identification with an X Modality (2020) — 430 citations
• Autoregressive Visual Tracking (2023) — 323 citations
• Class-Incremental Learning with Topological Schemas of Memory Spaces (2021) — 5 citations
• Multi-Target Multi-Camera Tracking by Tracklet-to-Target Assignment (2020) — 124 citations
• Bayesian Loss for Crowd Count Estimation With Point Supervision (2019) — 640 citations