Thomas Whelan
Computer Vision and Pattern Recognition · 2012–2019
A researcher in the Science corpus: 7 papers; trusts 266 researchers and is trusted by 106 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 113 citations into it; #3,088 of 21,575 by trust here, #2,857 by citations
- Aerospace Engineering — 95 citations into it; #234 of 6,421 by trust here, #307 by citations
- Geology — 37 citations into it; #35 of 687 by trust here, #32 by citations
- 3D Vision & Pose — 23 citations into it; #202 of 689 by trust here, #142 by citations
- Robotics & Control — 16 citations into it; #95 of 609 by trust here, #223 by citations
- Computer Graphics and Computer-Aided Design — 13 citations into it
- Computational Mechanics — 9 citations into it
- Control and Systems Engineering — 6 citations into it
Whom Thomas Whelan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Richard A. Newcombe
- Jürgen Sturm
- Andrew J. Davison
- Qian-Yi Zhou
- Shahram Izadi
- Frank Steinbrücker
- Christian Kerl
- Daniel Cremers
- Derek Hoiem
- Felix Endres
Who trusts Thomas Whelan overall
- Andrew J. Davison
- Olaf Kähler
- Hao Wang
- Ankur Handa
- Martin Rünz
- Vladlen Koltun
- Qian-Yi Zhou
- John McCormac
- Raul Mur-Artal
- Mahdi Yazdanpour
Papers from Thomas Whelan's perspective
Ordered by how strongly the researchers Thomas Whelan trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- The Replica Dataset: A Digital Replica of Indoor Spaces (2019) — 1,356 citations
- A benchmark for RGB-D visual odometry, 3D reconstruction and SLAM (2014) — 937 citations
- ElasticFusion: Dense SLAM Without A Pose Graph (2015) — 906 citations
- Robust real-time visual odometry for dense RGB-D mapping (2013) — 385 citations
- Real-time large-scale dense RGB-D SLAM with volumetric fusion (2014) — 497 citations
- ElasticFusion: Real-time dense SLAM and light source estimation (2016) — 711 citations
- Kintinuous: Spatially Extended KinectFusion (2012) — 729 citations