Lewei Yao

Computer Vision and Pattern Recognition · 2019–2024

A researcher in the Science corpus: 7 papers; trusts 864 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 298 citations into it; #14,262 of 21,575 by trust here, #5,375 by citations
• Artificial Intelligence — 201 citations into it; #23,210 of 35,345 by trust here, #8,999 by citations
• Model Architectures — 61 citations into it
• Evaluation & Benchmarks — 32 citations into it
• Large Language Models — 26 citations into it
• Generative Models — 25 citations into it
• Optimization & Training — 23 citations into it
• Natural Language Processing — 11 citations into it

Whom Lewei Yao trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Alex Krizhevsky
4. Geoffrey E. Hinton
5. Diederik P. Kingma
6. Tsung-Yi Lin
7. Ilya Sutskever
8. Yoshua Bengio
9. Shaoqing Ren
10. Karen Simonyan

Who trusts Lewei Yao overall

1. Matthias Minderer
2. Jianhua Han
3. Jingyi Zhang
4. Tianheng Cheng
5. Hang Xu
6. Yi Wang
7. Alexey A. Gritsenko
8. Xiaodan Liang
9. Muhammad Uzair Khattak
10. Hao Huang

Papers from Lewei Yao's perspective

Ordered by how strongly the researchers Lewei Yao 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. Long Short-Term Memory
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• FILIP: Fine-grained Interactive Language-Image Pre-Training (2021) — 865 citations
• Auto-FPN: Automatic Network Architecture Adaptation for Object Detection Beyond Classification (2019) — 199 citations
• PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis (2023) — 927 citations
• DetCLIP: Dictionary-Enriched Visual-Concept Paralleled Pre-training for Open-world Detection (2022) — 265 citations
• DetCLIPv2: Scalable Open-Vocabulary Object Detection Pre-training via Word-Region Alignment (2023) — 129 citations
• PixArt-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation (2024) — 340 citations
• SM-NAS: Structural-to-Modular Neural Architecture Search for Object Detection (2019) — 86 citations