Jiaqi Ma

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; #15,698 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 Jiaqi Ma trusts overall

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

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

Who trusts Jiaqi Ma overall

1. Runsheng Xu

Papers from Jiaqi Ma's perspective

Ordered by how strongly the researchers Jiaqi Ma 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

• 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