Hongdong Li
Computer Vision and Pattern Recognition · 2012–2022
A researcher in the Science corpus: 20 papers; trusts 1,597 researchers and is trusted by 108 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 539 citations into it; #3,184 of 21,575 by trust here, #2,594 by citations
- Artificial Intelligence — 132 citations into it
- Media Technology — 99 citations into it; #1,136 of 3,621 by trust here, #789 by citations
- Aerospace Engineering — 93 citations into it; #985 of 6,421 by trust here, #1,602 by citations
- Model Architectures — 53 citations into it
- Evaluation & Benchmarks — 42 citations into it
- Computational Mechanics — 34 citations into it; #5,926 of 10,001 by trust here, #6,582 by citations
- Representation & Self-Supervised Learning — 33 citations into it
Whom Hongdong Li trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Alex Krizhevsky
- Kaiming He
- David G. Lowe
- Karen Simonyan
- Andrew Zisserman
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
Who trusts Hongdong Li overall
- Yue Wang
- Zhedong Zheng
- Xiaoshui Huang
- Torsten Sattler
- Sijie Zhu
- Xingyu Jiang
- Jiayi Ma
- Tingyu Wang
- Paul-Edouard Sarlin
- Justin M. Solomon
Papers from Hongdong Li's perspective
Ordered by how strongly the researchers Hongdong Li 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- 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
- The Visual Object Tracking VOT2016 Challenge Results (2016) — 773 citations
- Learning to Estimate Hidden Motions with Global Motion Aggregation (2021) — 421 citations
- Neural Aggregation Network for Video Face Recognition (2016) — 397 citations
- A Simple Prior-Free Method for Non-rigid Structure-from-Motion Factorization (2012) — 369 citations
- Rotation Averaging (2013) — 632 citations
- Efficient Global 2D-3D Matching for Camera Localization in a Large-Scale 3D Map (2017) — 176 citations
- Kernel Methods on the Riemannian Manifold of Symmetric Positive Definite Matrices (2013) — 312 citations
- Learning Trajectory Dependencies for Human Motion Prediction (2019) — 559 citations
- Deep Stacked Hierarchical Multi-Patch Network for Image Deblurring (2019) — 649 citations
- Adversarial Spatio-Temporal Learning for Video Deblurring (2018) — 341 citations
- Deep Subspace Clustering Networks (2017) — 586 citations
- Deblurring by Realistic Blurring (2020) — 476 citations
- Word-level Deep Sign Language Recognition from Video: A New Large-scale Dataset and Methods Comparison (2019) — 648 citations
- Lending Orientation to Neural Networks for Cross-View Geo-Localization (2019) — 386 citations
- Deep Image Deblurring: A Survey (2022) — 385 citations
- Align and Prompt: Video-and-Language Pre-training with Entity Prompts (2021) — 230 citations
- Hierarchical Neural Architecture Search for Deep Stereo Matching (2020) — 429 citations
- Spatial-Aware Feature Aggregation for Image based Cross-View Geo-Localization (2019) — 313 citations
- Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration (2016) — 1,133 citations
- Go-ICP: Solving 3D Registration Efficiently and Globally Optimally (2013) — 506 citations