Ruimao Zhang

Computer Vision and Pattern Recognition · 2015–2022

A researcher in the Science corpus: 9 papers; trusts 598 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 204 citations into it; #19,973 of 21,575 by trust here, #7,750 by citations
• Artificial Intelligence — 75 citations into it; #33,835 of 35,345 by trust here, #16,471 by citations
• Computational Mechanics — 54 citations into it
• Model Architectures — 33 citations into it
• Optimization & Training — 19 citations into it
• Evaluation & Benchmarks — 17 citations into it
• Media Technology — 12 citations into it
• Oncology — 11 citations into it

Whom Ruimao Zhang trusts overall

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

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

Who trusts Ruimao Zhang overall

1. Shiv Ram Dubey
2. X. Wang
3. Wu-Jun Li
4. Cheng Deng
5. Qi Li
6. Faqiang Wang
7. Abhinav Kumar Gupta
8. Sheng Wang
9. Zhenan Sun
10. Xingchao Peng

Papers from Ruimao Zhang's perspective

Ordered by how strongly the researchers Ruimao Zhang trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
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. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• DeepFashion2: A Versatile Benchmark for Detection, Pose Estimation, Segmentation and Re-Identification of Clothing Images (2019) — 435 citations
• Cost-Effective Active Learning for Deep Image Classification (2017) — 750 citations
• Bit-Scalable Deep Hashing With Regularized Similarity Learning for Image Retrieval and Person Re-Identification (2015) — 492 citations
• SSN: Learning Sparse Switchable Normalization via SparsestMax (2019) — 57 citations
• Towards Photo-Realistic Virtual Try-On by Adaptively Generating↔Preserving Image Content (2020) — 337 citations
• AMOS: A Large-Scale Abdominal Multi-Organ Benchmark for Versatile Medical Image Segmentation (2022) — 574 citations
• 2DPASS: 2D Priors Assisted Semantic Segmentation on LiDAR Point Clouds (2022) — 338 citations
• Shallow Attention Network for Polyp Segmentation (2021) — 417 citations
• Sparse Single Sweep LiDAR Point Cloud Segmentation via Learning Contextual Shape Priors from Scene Completion (2020) — 383 citations