Carl Yuheng Ren

Computer Vision and Pattern Recognition · 2013–2019

A researcher in the Science corpus: 3 papers; trusts 20 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 39 citations into it; #7,459 of 21,575 by trust here, #5,236 by citations
• Aerospace Engineering — 28 citations into it; #1,363 of 6,421 by trust here, #764 by citations
• 3D Vision & Pose — 10 citations into it; #276 of 689 by trust here, #229 by citations
• Geology — 10 citations into it; #219 of 687 by trust here, #128 by citations
• Computer Graphics and Computer-Aided Design — 8 citations into it; #1,552 of 1,584 by trust here, #843 by citations

Whom Carl Yuheng Ren trusts overall

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

1. Richard A. Newcombe
2. Andrew J. Davison
3. Shahram Izadi
4. Brian Curless
5. Georg S. W. Klein
6. Pedro F. Felzenszwalb

Who trusts Carl Yuheng Ren overall

1. Andreas Geiger
2. João Carreira
3. Angela Dai
4. Ali O. Ulusoy
5. Sara Alexandra Gomes Vicente
6. Christopher Bongsoo Choy
7. Edward James Smith
8. JunYoung Gwak

Papers from Carl Yuheng Ren's perspective

Ordered by how strongly the researchers Carl Yuheng Ren trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Microsoft COCO: Common Objects in Context
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Object Detection with Discriminatively Trained Part Based Models
5. KinectFusion: Real-time dense surface mapping and tracking
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. A volumetric method for building complex models from range images
10. Gradient-based learning applied to document recognition

Their papers

• The Replica Dataset: A Digital Replica of Indoor Spaces (2019) — 1,356 citations
• Dense Reconstruction Using 3D Object Shape Priors (2013) — 164 citations
• Very High Frame Rate Volumetric Integration of Depth Images on Mobile Devices (2015) — 322 citations