Zerong Zheng
Computer Vision and Pattern Recognition · 2018–2022
A researcher in the Science corpus: 5 papers; trusts 484 researchers and is trusted by 9 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 162 citations into it; #9,828 of 21,575 by trust here, #11,083 by citations
- Computational Mechanics — 96 citations into it; #4,000 of 10,001 by trust here, #3,362 by citations
- Computer Graphics and Computer-Aided Design — 68 citations into it
- 3D Vision & Pose — 26 citations into it
- Control and Systems Engineering — 26 citations into it
- Aerospace Engineering — 19 citations into it
- Geology — 8 citations into it
- Artificial Intelligence — 6 citations into it
Whom Zerong Zheng trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Thiemo Alldieck
- Michael J. Black
- Geoffrey E. Hinton
- Kaiming He
- Gerard Pons-Moll
- Alex Krizhevsky
- Angjoo Kanazawa
- Ross B. Girshick
- Yoshua Bengio
Who trusts Zerong Zheng overall
- Yuliang Xiu
- Julian Chibane
- Jinlong Yang
- Bharat Lal Bhatnagar
- Yebin Liu
- Gerard Pons-Moll
- Thiemo Alldieck
- Shunsuke Saito
- Kaiwen Guo
- Qionghai Dai
Papers from Zerong Zheng's perspective
Ordered by how strongly the researchers Zerong Zheng 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
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- DeepHuman: 3D Human Reconstruction From a Single Image (2019) — 374 citations
- Tensor4D: Efficient Neural 4D Decomposition for High-Fidelity Dynamic Reconstruction and Rendering (2022) — 300 citations
- Function4D: Real-time Human Volumetric Capture from Very Sparse Consumer RGBD Sensors (2021) — 409 citations
- PaMIR: Parametric Model-Conditioned Implicit Representation for Image-Based Human Reconstruction (2020) — 376 citations
- DoubleFusion: Real-Time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor (2018) — 298 citations