Jongheon Jeong

Computer Vision and Pattern Recognition · 2020–2024

A researcher in the Science corpus: 6 papers; trusts 947 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 211 citations into it
• Artificial Intelligence — 190 citations into it; #19,200 of 35,345 by trust here, #14,438 by citations
• Representation & Self-Supervised Learning — 65 citations into it; #1,969 of 3,145 by trust here, #2,299 by citations
• Generative Models — 56 citations into it
• Optimization & Training — 28 citations into it
• Evaluation & Benchmarks — 25 citations into it
• Computer Networks and Communications — 19 citations into it
• Model Architectures — 18 citations into it

Whom Jongheon Jeong trusts overall

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

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

Who trusts Jongheon Jeong overall

1. Zhaopeng Gu
2. Gyuhak Kim
3. Ceyuan Yang
4. Bingke Zhu
5. Qihang Zhou
6. Sepideh Esmaeilpour
7. Guoyang Xie
8. Mert Kilickaya

Papers from Jongheon Jeong's perspective

Ordered by how strongly the researchers Jongheon Jeong 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. 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

• Training GANs with Stronger Augmentations via Contrastive Discriminator (2021) — 70 citations
• CSI: Novelty Detection via Contrastive Learning on Distributionally Shifted Instances (2020) — 745 citations
• Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think (2024) — 621 citations
• WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation (2023) — 563 citations
• SPot-the-Difference Self-Supervised Pre-training for Anomaly Detection and Segmentation (2022) — 729 citations
• NOTE: Robust Continual Test-time Adaptation Against Temporal Correlation (2022) — 209 citations