Runsheng Xu

Computer Vision and Pattern Recognition · 2021–2023

A researcher in the Science corpus: 5 papers; trusts 501 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 274 citations into it; #15,696 of 21,575 by trust here, #9,563 by citations
• Artificial Intelligence — 163 citations into it
• Generative Models — 127 citations into it
• Aerospace Engineering — 39 citations into it
• Model Architectures — 38 citations into it
• Statistical and Nonlinear Physics — 36 citations into it
• Automotive Engineering — 35 citations into it
• Probabilistic & Bayesian Methods — 32 citations into it

Whom Runsheng Xu trusts overall

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

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

Who trusts Runsheng Xu overall

1. Zhengzhong Tu
2. Hao Xiang
3. Xin Xia
4. Yue Hu
5. Jiaqi Ma
6. Shaoheng Fang

Papers from Runsheng Xu's perspective

Ordered by how strongly the researchers Runsheng Xu 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. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

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
• Diffusion Models: A Comprehensive Survey of Methods and Applications (2022) — 2,329 citations
• V2V4Real: A Real-World Large-Scale Dataset for Vehicle-to-Vehicle Cooperative Perception (2023) — 296 citations