Tianfan Xue
Computer Vision and Pattern Recognition · 2012–2018
A researcher in the Science corpus: 8 papers; trusts 838 researchers and is trusted by 1,820 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 265 citations into it; #944 of 21,575 by trust here, #1,353 by citations
- 3D Vision & Pose — 64 citations into it; #218 of 689 by trust here, #137 by citations
- Aerospace Engineering — 63 citations into it
- Computational Mechanics — 57 citations into it; #580 of 10,001 by trust here, #180 by citations
- Artificial Intelligence — 35 citations into it
- Generative Models — 32 citations into it; #450 of 1,956 by trust here, #267 by citations
- Computer Graphics and Computer-Aided Design — 30 citations into it
- Evaluation & Benchmarks — 30 citations into it
Whom Tianfan Xue trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Kaiming He
- Alex Krizhevsky
- Yann LeCun
- Yoshua Bengio
- Antonio Torralba
- David G. Lowe
- Ross B. Girshick
- Ilya Sutskever
Who trusts Tianfan Xue overall
- Jiajun Wu
- Simon Niklaus
- Jitendra Malik
- Andrea Vedaldi
- Chen Sun
- Josh Tenenbaum
- Jun-Yan Zhu
- Chelsea Finn
- Sergey Levine
- Angjoo Kanazawa
Papers from Tianfan Xue's perspective
Ordered by how strongly the researchers Tianfan Xue 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
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling (2016) — 2,154 citations
- Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks (2016) — 418 citations
- Single Image 3D Interpreter Network (2016) — 291 citations
- Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling (2018) — 524 citations
- MarrNet: 3D Shape Reconstruction via 2.5D Sketches (2017) — 440 citations
- Video Enhancement with Task-Oriented Flow (2017) — 1,736 citations
- Example-based 3D object reconstruction from line drawings (2012) — 37 citations
- Unprocessing Images for Learned Raw Denoising (2018) — 540 citations