Mingyang Shang

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 2 papers; trusts 67 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 29 citations into it; #19,112 of 21,575 by trust here, #17,258 by citations
• Computational Mechanics — 15 citations into it; #8,830 of 10,001 by trust here, #7,884 by citations
• 3D Vision & Pose — 9 citations into it
• Generative Models — 7 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Mingyang Shang trusts overall

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

1. Karen Simonyan
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Chin-Yew Lin
6. Diederik P. Kingma
7. Alexey Dosovitskiy
8. Andrew Zisserman
9. Kaiming He
10. Yann LeCun

Who trusts Mingyang Shang overall

1. Jonathan Sauder
2. Yongming Rao
3. Hanchen Wang

Papers from Mingyang Shang's perspective

Ordered by how strongly the researchers Mingyang Shang 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Y^2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences (2018) — 62 citations
• View Inter-Prediction GAN: Unsupervised Representation Learning for 3D Shapes by Learning Global Shape Memories to Support Local View Predictions (2018) — 143 citations