Weikai Chen
Computer Vision and Pattern Recognition · 2018–2019
A researcher in the Science corpus: 4 papers; trusts 414 researchers and is trusted by 28 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 140 citations into it; #5,616 of 21,575 by trust here, #6,089 by citations
- Computational Mechanics — 71 citations into it; #1,818 of 10,001 by trust here, #1,237 by citations
- Computer Graphics and Computer-Aided Design — 51 citations into it; #324 of 1,584 by trust here, #376 by citations
- 3D Vision & Pose — 50 citations into it; #501 of 689 by trust here, #421 by citations
- Aerospace Engineering — 22 citations into it
- Control and Systems Engineering — 11 citations into it
- Generative Models — 10 citations into it
- Artificial Intelligence — 9 citations into it
Whom Weikai Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Sergey Ioffe
- Jitendra Malik
- Shubham Tulsiani
- Ilya Sutskever
- Yoshua Bengio
- Jimmy Ba
Who trusts Weikai Chen overall
- Michael Niemeyer
- Jeremy Reizenstein
- Lingjie Liu
- Alex Yu
- Wenzheng Chen
- Shunsuke Saito
- Philipp Henzler
- Matthew Tancik
- Shichen Liu
- Zerong Zheng
Papers from Weikai Chen's perspective
Ordered by how strongly the researchers Weikai Chen 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)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Soft Rasterizer: A Differentiable Renderer for Image-Based 3D Reasoning (2019) — 812 citations
- Learning to Infer Implicit Surfaces without 3D Supervision (2019) — 213 citations
- Soft Rasterizer: Differentiable Rendering for Unsupervised Single-View Mesh Reconstruction (2019) — 100 citations
- Deep Volumetric Video From Very Sparse Multi-view Performance Capture (2018) — 128 citations