Tengfei Wang

Computer Vision and Pattern Recognition · European Conference on Computer Vision · 2021–2024

A researcher in the Science corpus: 5 papers; trusts 409 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 202 citations into it; #21,510 of 21,575 by trust here, #6,371 by citations
• Generative Models — 106 citations into it
• Computer Graphics and Computer-Aided Design — 73 citations into it; #1,577 of 1,584 by trust here, #499 by citations
• Artificial Intelligence — 48 citations into it
• Statistical and Nonlinear Physics — 16 citations into it
• Biophysics — 9 citations into it
• Optimization & Training — 9 citations into it
• Evaluation & Benchmarks — 7 citations into it

Whom Tengfei Wang trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jonathan Ho
4. Kaiming He
5. Alex Krizhevsky
6. Yoshua Bengio
7. Tero Karras
8. Yann LeCun
9. Ilya Sutskever
10. Jimmy Ba

Who trusts Tengfei Wang overall

1. Peng Wang
2. Yuval Alaluf
3. Gwanghyun Kim
4. Guillaume Couairon
5. Yichun Shi
6. Lvmin Zhang
7. Wenhu Chen
8. Duygu Ceylan
9. Narek Tumanyan
10. Florinel-Alin Croitoru

Papers from Tengfei Wang's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Pretraining is All You Need for Image-to-Image Translation (2022) — 216 citations
• High-Fidelity GAN Inversion for Image Attribute Editing (2021) — 305 citations
• Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior (2023) — 420 citations
• RODIN: A Generative Model for Sculpting 3D Digital Avatars Using Diffusion (2022) — 393 citations
• LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation (2024) — 817 citations