Weihao Yu
Computer Vision and Pattern Recognition · 2018–2024
A researcher in the Science corpus: 11 papers; trusts 1,526 researchers and is trusted by 14 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 484 citations into it; #8,072 of 21,575 by trust here, #2,435 by citations
- Artificial Intelligence — 439 citations into it; #19,319 of 35,345 by trust here, #3,138 by citations
- Model Architectures — 214 citations into it; #1,449 of 2,278 by trust here, #454 by citations
- Natural Language Processing — 96 citations into it
- Large Language Models — 78 citations into it
- Evaluation & Benchmarks — 70 citations into it
- Optimization & Training — 64 citations into it
- Multimodal Learning — 53 citations into it
Whom Weihao Yu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Ross B. Girshick
- Diederik P. Kingma
- Ilya Sutskever
- Yoshua Bengio
- Karen Simonyan
- Christian Szegedy
- Yann LeCun
Who trusts Weihao Yu overall
- Jianwei Yang
- Siyuan Wang
- Xinchao Wang
- Yanyu Li
- Pan Zhou
- Penghao Wu
- Dingkang Liang
- Hanmeng Liu
- Ao Wang
- Bo Li
Papers from Weihao Yu's perspective
Ordered by how strongly the researchers Weihao Yu trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet (2021) — 2,523 citations
- Knowledge-Embedded Routing Network for Scene Graph Generation (2019) — 425 citations
- MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities (2023) — 1,322 citations
- Refiner: Refining Self-attention for Vision Transformers (2021) — 69 citations
- ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning (2020) — 343 citations
- MambaOut: Do We Really Need Mamba for Vision?* (2024) — 309 citations
- InceptionNeXt: When Inception Meets ConvNeXt (2023) — 350 citations
- Inception Transformer (2022) — 300 citations
- MetaFormer Baselines for Vision (2022) — 348 citations
- MetaFormer is Actually What You Need for Vision (2021) — 1,389 citations
- Deep Reasoning with Knowledge Graph for Social Relationship Understanding (2018) — 196 citations