Yumao Lu
Computer Vision and Pattern Recognition · 2021–2023
A researcher in the Science corpus: 8 papers; trusts 1,040 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 446 citations into it; #15,244 of 21,575 by trust here, #2,966 by citations
- Artificial Intelligence — 379 citations into it; #25,239 of 35,345 by trust here, #3,998 by citations
- Multimodal Learning — 259 citations into it; #1,000 of 1,211 by trust here, #411 by citations
- Natural Language Processing — 75 citations into it
- Evaluation & Benchmarks — 73 citations into it
- Representation & Self-Supervised Learning — 73 citations into it
- Large Language Models — 58 citations into it
- Model Architectures — 57 citations into it
Whom Yumao Lu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ross B. Girshick
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Yann LeCun
- Karen Simonyan
- Shaoqing Ren
Who trusts Yumao Lu overall
Papers from Yumao Lu's perspective
Ordered by how strongly the researchers Yumao Lu 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
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
Their papers
- Florence: A New Foundation Model for Computer Vision (2021) — 1,142 citations
- An Empirical Study of GPT-3 for Few-Shot Knowledge-Based VQA (2021) — 537 citations
- Scaling Up Vision-Language Pretraining for Image Captioning (2021) — 335 citations
- UFO: A UniFied TransfOrmer for Vision-Language Representation Learning (2021) — 65 citations
- UniTAB: Unifying Text and Box Outputs for Grounded Vision-Language Modeling (2021) — 147 citations
- SwinBERT: End-to-End Transformers with Sparse Attention for Video Captioning (2021) — 341 citations
- Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks (2023) — 565 citations
- Crossing the Format Boundary of Text and Boxes: Towards Unified Vision-Language Modeling (2021) — 39 citations