Richard Bowden

Computer Vision and Pattern Recognition · 2001–2021

A researcher in the Science corpus: 20 papers; trusts 1,154 researchers and is trusted by 62 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 381 citations into it; #3,644 of 21,575 by trust here, #2,468 by citations
• Artificial Intelligence — 274 citations into it
• Reinforcement Learning — 55 citations into it
• Model Architectures — 53 citations into it; #589 of 2,278 by trust here, #1,665 by citations
• Aerospace Engineering — 43 citations into it
• Natural Language Processing — 43 citations into it
• Control and Systems Engineering — 42 citations into it
• Causal Inference & Discovery — 41 citations into it

Whom Richard Bowden trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Yoshua Bengio
4. Alex Krizhevsky
5. Yann LeCun
6. Ilya Sutskever
7. Alex Graves
8. Kaiming He
9. Radford M. Neal
10. J. Urgen Schmidhuber

Who trusts Richard Bowden overall

1. Thierry Bouwmans
2. Oscar Koller
3. Necati Cihan Camgöz
4. Pichao Wang
5. Yu Kong
6. Xiaodong Yang
7. P. PramodKumar
8. Andrews Cordolino Sobral
9. Xi Chen
10. Olivier Barnich

Papers from Richard Bowden's perspective

Ordered by how strongly the researchers Richard Bowden 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. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
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

• The Visual Object Tracking VOT2015 Challenge Results (2015) — 901 citations
• The Visual Object Tracking VOT2014 Challenge Results (2014) — 512 citations
• The Visual Object Tracking VOT2017 Challenge Results (2017) — 301 citations
• The Sixth Visual Object Tracking VOT2018 Challenge Results (2018) — 797 citations
• An Improved Adaptive Background Mixture Model for Real-time Tracking with Shadow Detection (2001)
• A boosted classifier tree for hand shape detection (2004) — 303 citations
• Putting the pieces together: Connected Poselets for human pose estimation (2011) — 39 citations
• Hollywood 3D: Recognizing Actions in 3D Natural Scenes (2013) — 106 citations
• Sign Language Transformers: Joint End-to-End Sign Language Recognition and Translation (2020) — 771 citations
• A Survey of Deep Learning Applications to Autonomous Vehicle Control (2019) — 696 citations
• Neural Sign Language Translation (2018) — 863 citations
• Kinecting the dots: Particle based scene flow from depth sensors (2011) — 110 citations
• Using Convolutional 3D Neural Networks for User-independent continuous gesture recognition (2016) — 98 citations
• SubUNets: End-to-End Hand Shape and Continuous Sign Language Recognition (2017) — 335 citations
• D’ya Like DAGs? A Survey on Structure Learning and Causal Discovery (2021) — 400 citations
• Weakly Supervised Learning with Multi-Stream CNN-LSTM-HMMs to Discover Sequential Parallelism in Sign Language Videos (2020) — 365 citations
• Exploring Causal Relationships in Visual Object Tracking (2015) — 15 citations
• Scene Particles: Unregularized Particle Based Scene Flow Estimation. (2013) — 29 citations
• Sign Language Recognition (2011) — 425 citations
• Spelling it out: Real-time ASL fingerspelling recognition (2011) — 429 citations