Tobias Weyand
Computer Vision and Pattern Recognition · 2012–2020
A researcher in the Science corpus: 7 papers; trusts 1,151 researchers and is trusted by 1,664 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 257 citations into it; #1,006 of 21,575 by trust here, #590 by citations
- Aerospace Engineering — 105 citations into it; #780 of 6,421 by trust here, #1,224 by citations
- Artificial Intelligence — 45 citations into it
- Information Retrieval & Search — 41 citations into it
- Media Technology — 39 citations into it
- Model Architectures — 26 citations into it
- Evaluation & Benchmarks — 15 citations into it; #1,887 of 3,147 by trust here, #2,009 by citations
- Representation & Self-Supervised Learning — 10 citations into it
Whom Tobias Weyand trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David G. Lowe
- Andrew Zisserman
- Kaiming He
- Herv'e J'egou
- Ondřej Chum
- Christian Szegedy
- Josef Sivic
- Geoffrey E. Hinton
- Alex Krizhevsky
- Yunpeng Li
Who trusts Tobias Weyand overall
- Paul Hongsuck Seo
- Paul-Edouard Sarlin
- Barret Zoph
- Zhipeng Cai
- Chen Sun
- Giorgos Tolias
- Jack Sim
- Bingyi Cao
- Quoc V. Le
- Andrew G. Howard
Papers from Tobias Weyand's perspective
Ordered by how strongly the researchers Tobias Weyand trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications (2017) — 25,507 citations
- PlaNet - Photo Geolocation with Convolutional Neural Networks (2016) — 494 citations
- Image Retrieval for Image-Based Localization Revisited (2012) — 314 citations
- Large-Scale Image Retrieval with Attentive Deep Local Features (2016) — 860 citations
- Google Landmarks Dataset v2 – A Large-Scale Benchmark for Instance-Level Recognition and Retrieval (2020) — 477 citations
- CPlaNet: Enhancing Image Geolocalization by Combinatorial Partitioning of Maps (2018) — 112 citations
- Visual landmark recognition from Internet photo collections: A large-scale evaluation (2014) — 38 citations