Dushyant Mehta

Computer Vision and Pattern Recognition · 2016–2017

A researcher in the Science corpus: 7 papers; trusts 750 researchers and is trusted by 108 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 312 citations into it; #3,191 of 21,575 by trust here, #3,280 by citations
• Human-Computer Interaction — 89 citations into it; #1,008 of 2,253 by trust here, #335 by citations
• Artificial Intelligence — 58 citations into it
• Control and Systems Engineering — 44 citations into it
• 3D Vision & Pose — 43 citations into it
• Biomedical Engineering — 41 citations into it
• Aerospace Engineering — 24 citations into it
• Model Architectures — 22 citations into it

Whom Dushyant Mehta trusts overall

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

1. Kaiming He
2. Mykhaylo Andriluka
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Ross B. Girshick
6. Yann LeCun
7. Sam Johnson
8. Diederik P. Kingma
9. Andrew Zisserman
10. Christian Szegedy

Who trusts Dushyant Mehta overall

1. Gyeongsik Moon
2. Muhammed Kocabas
3. Xiao Sun
4. Michael J. Black
5. Angjoo Kanazawa
6. Kyoung Mu Lee
7. Ce Zheng
8. Georgios Pavlakos
9. Kevin Qinghong Lin
10. Xingyi Zhou

Papers from Dushyant Mehta's perspective

Ordered by how strongly the researchers Dushyant Mehta 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
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

• Monocular 3D Human Pose Estimation in the Wild Using Improved CNN Supervision (2016) — 1,341 citations
• GANerated Hands for Real-Time 3D Hand Tracking from Monocular RGB (2017) — 565 citations
• VNect (2017) — 874 citations
• Real-Time Hand Tracking under Occlusion from an Egocentric RGB-D Sensor (2017) — 333 citations
• Single-Shot Multi-person 3D Pose Estimation from Monocular RGB (2017) — 460 citations
• Deep Shading: Convolutional Neural Networks for Screen Space Shading (2016) — 175 citations
• Monocular 3D Human Pose Estimation Using Transfer Learning and Improved CNN Supervision (2016) — 51 citations