Xin Xia

Computer Vision and Pattern Recognition · European Conference on Computer Vision · 2021–2023

A researcher in the Science corpus: 3 papers; trusts 136 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 80 citations into it; #15,780 of 21,575 by trust here, #15,529 by citations
• Aerospace Engineering — 34 citations into it
• Automotive Engineering — 29 citations into it
• Artificial Intelligence — 21 citations into it
• Environmental Engineering — 12 citations into it
• Computational Mechanics — 10 citations into it
• Geology — 8 citations into it
• 3D Vision & Pose — 6 citations into it

Whom Xin Xia trusts overall

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

1. Diederik P. Kingma
2. Qi Chen
3. Geoffrey E. Hinton
4. Jimmy Ba
5. Kaiming He
6. Alex Krizhevsky
7. Ross B. Girshick
8. Yoshua Bengio
9. Yann LeCun
10. Karen Simonyan

Who trusts Xin Xia overall

1. Runsheng Xu

Papers from Xin Xia's perspective

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

Their papers

• 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