Zehao Yu
Computer Vision and Pattern Recognition · 2017–2024
A researcher in the Science corpus: 6 papers; trusts 388 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 183 citations into it; #20,849 of 21,575 by trust here, #11,083 by citations
- Computer Graphics and Computer-Aided Design — 100 citations into it; #1,559 of 1,584 by trust here, #605 by citations
- Computational Mechanics — 81 citations into it; #9,855 of 10,001 by trust here, #3,029 by citations
- 3D Vision & Pose — 53 citations into it
- Aerospace Engineering — 43 citations into it
- Artificial Intelligence — 24 citations into it
- Generative Models — 14 citations into it
- Geology — 11 citations into it
Whom Zehao Yu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Jonathan T. Barron
- Andreas Geiger
- Geoffrey E. Hinton
- Songyou Peng
- Alex Krizhevsky
- Kaiming He
- Michael Niemeyer
- Yann LeCun
- Ben Mildenhall
Who trusts Zehao Yu overall
- Hengyi Wang
- Kerui Ren
- Guangcong Wang
- Shuzhe Wang
- Wenjing Bian
- Ze Yang
- Xiao Fu
- Lourdes de Agapito
- Vickie Ye
- Lihan Jiang
Papers from Zehao Yu's perspective
Ordered by how strongly the researchers Zehao 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)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- GENERATIVE ADVERSARIAL NETS
Their papers
- MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstruction (2022) — 647 citations
- TransFuser: Imitation With Transformer-Based Sensor Fusion for Autonomous Driving (2022) — 755 citations
- Deep Stock Representation Learning: From Candlestick Charts to Investment Decisions (2017) — 51 citations
- Gaussian Opacity Fields: Efficient Adaptive Surface Reconstruction in Unbounded Scenes (2024) — 318 citations
- 2D Gaussian Splatting for Geometrically Accurate Radiance Fields (2024) — 1,465 citations
- Mip-Splatting: Alias-Free 3D Gaussian Splatting (2023) — 860 citations