Yinghao Xu

Computer Vision and Pattern Recognition · 2020–2024

A researcher in the Science corpus: 11 papers; trusts 1,269 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 472 citations into it; #12,861 of 21,575 by trust here, #5,507 by citations
• Generative Models — 152 citations into it; #1,945 of 1,956 by trust here, #1,435 by citations
• Artificial Intelligence — 147 citations into it; #35,136 of 35,345 by trust here, #23,731 by citations
• Computer Graphics and Computer-Aided Design — 130 citations into it
• Computational Mechanics — 82 citations into it
• Representation & Self-Supervised Learning — 82 citations into it
• 3D Vision & Pose — 42 citations into it
• Evaluation & Benchmarks — 33 citations into it

Whom Yinghao Xu trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Alex Krizhevsky
5. Ross B. Girshick
6. Yoshua Bengio
7. Yann LeCun
8. Karen Simonyan
9. Ilya Sutskever
10. Andrew Zisserman

Who trusts Yinghao Xu overall

1. Ceyuan Yang
2. Jiapeng Zhu
3. Yujun Shen
4. Yotam Nitzan
5. Shekoofeh Azizi
6. Rinon Gal
7. Qingyan Bai
8. Jiale Xu
9. Chenlin Meng
10. Weihao Xia

Papers from Yinghao Xu's perspective

Ordered by how strongly the researchers Yinghao Xu 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Video Representation Learning with Visual Tempo Consistency (2020) — 94 citations
• Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humans (2020) — 874 citations
• Generative Hierarchical Features from Synthesizing Images (2020) — 126 citations
• Temporal Pyramid Network for Action Recognition (2020) — 445 citations
• Learning Object-Compositional Neural Radiance Field for Editable Scene Rendering (2021) — 309 citations
• Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model (2023) — 433 citations
• Data-Efficient Instance Generation from Instance Discrimination (2021) — 97 citations
• High-fidelity GAN Inversion with Padding Space (2022) — 34 citations
• One-Shot Generative Domain Adaptation (2021) — 69 citations
• CameraCtrl: Enabling Camera Control for Text-to-Video Generation (2024) — 425 citations
• GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generation (2024) — 333 citations