Xinbo Gao

Computer Vision and Pattern Recognition · 2010–2020

A researcher in the Science corpus: 16 papers; trusts 1,185 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 365 citations into it; #4,276 of 21,575 by trust here, #3,323 by citations
• Media Technology — 136 citations into it; #437 of 3,621 by trust here, #385 by citations
• Artificial Intelligence — 54 citations into it
• Computational Mechanics — 40 citations into it
• Evaluation & Benchmarks — 38 citations into it
• Generative Models — 30 citations into it
• Model Architectures — 25 citations into it
• Representation & Self-Supervised Learning — 20 citations into it

Whom Xinbo Gao trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Diederik P. Kingma
5. Karen Simonyan
6. Yoshua Bengio
7. A. Bovik
8. Ross B. Girshick
9. Yann LeCun
10. Zhou Wang

Who trusts Xinbo Gao overall

1. Kamal Nasrollahi
2. Jongyoo Kim
3. Jie Liu
4. Zhisheng Lu
5. Subeesh Vasu
6. Thomas Baltzer Moeslund
7. Yong Guo
8. Tong Tong
9. Zheng Zhang
10. Bee Lim

Papers from Xinbo Gao's perspective

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

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

Their papers

• A survey of graph edit distance (2010) — 817 citations
• Image Fine-grained Inpainting (2020) — 58 citations
• Triplet-Based Deep Hashing Network for Cross-Modal Retrieval (2018) — 371 citations
• Ordinal Regression with Multiple Output CNN for Age Estimation (2016) — 696 citations
• Self-Supervised Adversarial Hashing Networks for Cross-Modal Retrieval (2018) — 410 citations
• Lightweight Image Super-Resolution with Information Multi-distillation Network (2019) — 1,190 citations
• Fast and Accurate Single Image Super-Resolution via Information Distillation Network (2018) — 876 citations
• A Comprehensive Survey to Face Hallucination (2013) — 350 citations
• AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results (2019) — 62 citations
• Pairwise Relationship Guided Deep Hashing for Cross-Modal Retrieval (2017) — 336 citations
• Image Super-Resolution With Sparse Neighbor Embedding (2012) — 335 citations
• Channel-Wise and Spatial Feature Modulation Network for Single Image Super-Resolution (2018) — 294 citations
• Blind Image Quality Assessment via Deep Learning (2015) — 373 citations
• Multi-scale dictionary for single image super-resolution (2012) — 132 citations
• Single Image Super-Resolution With Non-Local Means and Steering Kernel Regression (2012) — 574 citations
• A multi-frame image super-resolution method (2010) — 297 citations