Xiaopeng Hong

Computer Vision and Pattern Recognition · 2015–2022

A researcher in the Science corpus: 17 papers; trusts 1,415 researchers and is trusted by 36 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 426 citations into it; #4,257 of 21,575 by trust here, #3,280 by citations
• Artificial Intelligence — 317 citations into it; #5,492 of 35,345 by trust here, #4,829 by citations
• Meta & Continual Learning — 110 citations into it; #132 of 1,041 by trust here, #113 by citations
• Representation & Self-Supervised Learning — 89 citations into it
• Model Architectures — 44 citations into it
• Radiology, Nuclear Medicine and Imaging — 35 citations into it; #1,069 of 3,265 by trust here, #1,136 by citations
• Optimization & Training — 34 citations into it
• Biomedical Engineering — 29 citations into it

Whom Xiaopeng Hong trusts overall

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

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

Who trusts Xiaopeng Hong overall

1. Da-Wei Zhou
2. Xiaoyu Tao
3. Liyuan Wang
4. Han-Jia Ye
5. Songlin Dong
6. Tyler L. Hayes
7. Xinyuan Chang
8. Hanbin Zhao
9. De-chuan Zhan
10. Kuilin Chen

Papers from Xiaopeng Hong's perspective

Ordered by how strongly the researchers Xiaopeng Hong 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Few-Shot Class-Incremental Learning (2020) — 556 citations
• Topology-Preserving Class-Incremental Learning (2020) — 203 citations
• Few-Shot Class-Incremental Learning via Relation Knowledge Distillation (2021) — 224 citations
• S-Prompts Learning with Pre-trained Transformers: An Occam's Razor for Domain Incremental Learning (2022) — 371 citations
• Class Incremental Learning for Video Action Classification (2021) — 8 citations
• Infrared-Visible Cross-Modal Person Re-Identification with an X Modality (2020) — 430 citations
• Remote Heart Rate Measurement From Highly Compressed Facial Videos: An End-to-End Deep Learning Solution With Video Enhancement (2019) — 332 citations
• Towards Reading Hidden Emotions: A Comparative Study of Spontaneous Micro-Expression Spotting and Recognition Methods (2015) — 392 citations
• A Continual Deepfake Detection Benchmark: Dataset, Methods, and Essentials (2022) — 87 citations
• Class-Incremental Learning with Topological Schemas of Memory Spaces (2021) — 5 citations
• Analogy-Detail Networks for Object Recognition (2020) — 9 citations
• Bi-Objective Continual Learning: Learning 'New' While Consolidating 'Known' (2020) — 31 citations
• Multi-Target Multi-Camera Tracking by Tracklet-to-Target Assignment (2020) — 124 citations
• Learning Graph Convolutional Network for Skeleton-based Human Action Recognition by Neural Searching (2019) — 367 citations
• A Boost in Revealing Subtle Facial Expressions: A Consolidated Eulerian Framework (2019) — 40 citations
• Bayesian Loss for Crowd Count Estimation With Point Supervision (2019) — 640 citations
• Video Action Recognition Via Neural Architecture Searching (2019) — 39 citations