Tony Tung

Computer Vision and Pattern Recognition · 2020

A researcher in the Science corpus: 1 paper; trusts 44 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 33 citations into it
• Computational Mechanics — 23 citations into it
• Computer Graphics and Computer-Aided Design — 15 citations into it

Whom Tony Tung trusts

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

1. Michael J. Black (in Computer Vision and Pattern Recognition)
2. Jitendra Malik (in Computer Vision and Pattern Recognition)
3. Jean Ponce (in Computer Vision and Pattern Recognition)
4. Andrew Zisserman (in Computer Vision and Pattern Recognition)
5. Kaiming He (in Computer Vision and Pattern Recognition)
6. Ross B. Girshick (in Computer Vision and Pattern Recognition)
7. Jia Deng (in Computer Vision and Pattern Recognition)
8. Cordelia Schmid (in Computer Vision and Pattern Recognition)
9. Thomas Brox (in Computer Vision and Pattern Recognition)
10. Alex Krizhevsky (in Computer Vision and Pattern Recognition)

Papers from Tony Tung's perspective

Ordered by how strongly the researchers Tony Tung 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. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Stacked Hourglass Networks for Human Pose Estimation
6. ImageNet: A large-scale hierarchical image database
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• ARCH: Animatable Reconstruction of Clothed Humans (2020) — 384 citations