Ruiping Wang

Computer Vision and Pattern Recognition · International Journal of Computer Vision · 2008–2023

A researcher in the Science corpus: 13 papers; trusts 1,272 researchers and is trusted by 40 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 349 citations into it; #4,252 of 21,575 by trust here, #5,013 by citations
• Artificial Intelligence — 173 citations into it
• Media Technology — 67 citations into it; #632 of 3,621 by trust here, #1,111 by citations
• Representation & Self-Supervised Learning — 42 citations into it
• Natural Language Processing — 36 citations into it
• Evaluation & Benchmarks — 32 citations into it
• Multimodal Learning — 31 citations into it
• Model Architectures — 28 citations into it

Whom Ruiping Wang trusts overall

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

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

Who trusts Ruiping Wang overall

1. Zhiwu Huang
2. Jiwen Lu
3. Ruiping Wang
4. Shiguang Shan
5. Xilin Chen
6. Eden Belouadah
7. Yap-Peng Tan
8. G. Wang
9. Munawar Hayat
10. Luc Van Gool

Papers from Ruiping Wang's perspective

Ordered by how strongly the researchers Ruiping Wang 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. ImageNet: A large-scale hierarchical image database
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
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. Going deeper with convolutions

Their papers

• Structure Inference Net: Object Detection Using Scene-Level Context and Instance-Level Relationships (2018) — 242 citations
• Learning Expressionlets on Spatio-temporal Manifold for Dynamic Facial Expression Recognition (2014) — 366 citations
• Deeply Learning Deformable Facial Action Parts Model for Dynamic Expression Analysis (2014) — 322 citations
• Multi-Modal Graph Neural Network for Joint Reasoning on Vision and Scene Text (2020) — 132 citations
• Deep Supervised Hashing for Fast Image Retrieval (2016) — 960 citations
• Projection Metric Learning on Grassmann Manifold with Application to Video based Face Recognition (2015) — 250 citations
• Manifold-Manifold Distance with application to face recognition based on image set (2008) — 445 citations
• Manifold Discriminant Analysis (2009) — 308 citations
• RingMo: A Remote Sensing Foundation Model With Masked Image Modeling (2023) — 413 citations
• FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery (2021) — 563 citations
• From Two Graphs to N Questions: A VQA Dataset for Compositional Reasoning on Vision and Commonsense (2019) — 13 citations
• Exemplar-Supported Generative Reproduction for Class Incremental Learning (2018) — 90 citations
• Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification (2015) — 264 citations