Hao Xiang
Computer Vision and Pattern Recognition · 2021–2023
A researcher in the Science corpus: 4 papers; trusts 272 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 114 citations into it; #15,697 of 21,575 by trust here, #13,815 by citations
- Artificial Intelligence — 41 citations into it
- Aerospace Engineering — 38 citations into it
- Automotive Engineering — 35 citations into it
- Model Architectures — 27 citations into it
- Environmental Engineering — 13 citations into it
- Computational Mechanics — 12 citations into it
- Optimization & Training — 11 citations into it
Whom Hao Xiang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Kaiming He
- Geoffrey E. Hinton
- Jimmy Ba
- Alex Krizhevsky
- Ross B. Girshick
- Qi Chen
- Yoshua Bengio
- Yann LeCun
- Karen Simonyan
Who trusts Hao Xiang overall
Papers from Hao Xiang's perspective
Ordered by how strongly the researchers Hao Xiang 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
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Going deeper with convolutions
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- CoBEVT: Cooperative Bird's Eye View Semantic Segmentation with Sparse Transformers (2022) — 398 citations
- V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer (2022) — 684 citations
- OPV2V: An Open Benchmark Dataset and Fusion Pipeline for Perception with Vehicle-to-Vehicle Communication (2021) — 664 citations
- V2V4Real: A Real-World Large-Scale Dataset for Vehicle-to-Vehicle Cooperative Perception (2023) — 296 citations