Mingg-Ming Cheng

Computer Vision and Pattern Recognition · 2021–2023

A researcher in the Science corpus: 7 papers; trusts 1,293 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 389 citations into it; #21,300 of 21,575 by trust here, #8,409 by citations
• Artificial Intelligence — 246 citations into it
• Meta & Continual Learning — 94 citations into it
• Model Architectures — 87 citations into it
• Radiology, Nuclear Medicine and Imaging — 38 citations into it
• Generative Models — 37 citations into it
• Representation & Self-Supervised Learning — 36 citations into it
• Optimization & Training — 32 citations into it

Whom Mingg-Ming Cheng trusts overall

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

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

Who trusts Mingg-Ming Cheng overall

1. Zhaohui Zheng

Papers from Mingg-Ming Cheng's perspective

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

Their papers

• Vision Permutator: A Permutable MLP-Like Architecture for Visual Recognition (2021) — 251 citations
• Masked Diffusion Transformer is a Strong Image Synthesizer (2023) — 312 citations
• P2T: Pyramid Pooling Transformer for Scene Understanding (2021) — 313 citations
• Representation Compensation Networks for Continual Semantic Segmentation (2022) — 143 citations
• Endpoints Weight Fusion for Class Incremental Semantic Segmentation (2023) — 77 citations
• Long-Tailed Class Incremental Learning (2022) — 60 citations
• Low-Light Image and Video Enhancement Using Deep Learning: A Survey (2021) — 573 citations