Wadim Kehl

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 5 papers; trusts 554 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 125 citations into it; #10,179 of 21,575 by trust here, #9,563 by citations
• Aerospace Engineering — 55 citations into it; #2,494 of 6,421 by trust here, #2,367 by citations
• Artificial Intelligence — 36 citations into it
• Computer Graphics and Computer-Aided Design — 15 citations into it
• Computational Mechanics — 13 citations into it; #4,751 of 10,001 by trust here, #4,937 by citations
• Evaluation & Benchmarks — 12 citations into it
• Representation & Self-Supervised Learning — 12 citations into it
• Generative Models — 11 citations into it

Whom Wadim Kehl trusts overall

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

1. Kaiming He
2. Ross B. Girshick
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yann LeCun
6. Karen Simonyan
7. Diederik P. Kingma
8. Yoshua Bengio
9. David G. Lowe
10. Tsung-Yi Lin

Who trusts Wadim Kehl overall

1. Bugra Tekin
2. Sergey Zakharov
3. Yu Xiang
4. Andrea Simonelli
5. Yann Labb'e
6. Martin Sundermeyer
7. Jonah Philion
8. Shichao Yang
9. Kiru Park
10. Gu Wang

Papers from Wadim Kehl's perspective

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

Their papers

• SSD-6D: Making RGB-Based 3D Detection and 6D Pose Estimation Great Again (2017) — 1,003 citations
• DeceptionNet: Network-Driven Domain Randomization (2019) — 100 citations
• BOP: Benchmark for 6D Object Pose Estimation (2018) — 544 citations
• ROI-10D: Monocular Lifting of 2D Detection to 6D Pose and Metric Shape (2018) — 302 citations
• An Octree-Based Approach towards Efficient Variational Range Data Fusion (2016) — 7 citations