Weilong Yang

Computer Vision and Pattern Recognition · 2010–2021

A researcher in the Science corpus: 9 papers; trusts 1,016 researchers and is trusted by 98 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 264 citations into it; #3,282 of 21,575 by trust here, #6,146 by citations
• Artificial Intelligence — 170 citations into it; #10,218 of 35,345 by trust here, #10,798 by citations
• Generative Models — 90 citations into it
• Optimization & Training — 53 citations into it
• Evaluation & Benchmarks — 23 citations into it
• Safety, Robustness & Interpretability — 21 citations into it
• Representation & Self-Supervised Learning — 19 citations into it
• Model Architectures — 15 citations into it

Whom Weilong Yang trusts overall

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

1. Pedro F. Felzenszwalb
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Kaiming He
5. Diederik P. Kingma
6. Deva Ramanan
7. Yoshua Bengio
8. Christian Szegedy
9. Ross B. Girshick
10. Navneet Dalal

Who trusts Weilong Yang overall

1. Hema Swetha Koppula
2. Yang Wang
3. Guo-qing Guo
4. Michalis Raptis
5. Chaitanya Desai
6. Deva Ramanan
7. Christopher Ellis
8. Syed Zain Masood
9. Marcus Rohrbach
10. Mateusz Malinowski

Papers from Weilong Yang's perspective

Ordered by how strongly the researchers Weilong Yang 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. 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

• Recognizing human actions from still images with latent poses (2010) — 233 citations
• Regularizing Generative Adversarial Networks under Limited Data (2021) — 185 citations
• Image Retrieval with Structured Object Queries Using Latent Ranking SVM (2012) — 58 citations
• Discriminative Latent Models for Recognizing Contextual Group Activities (2012) — 318 citations
• RetrieveGAN: Image Synthesis via Differentiable Patch Retrieval (2020) — 57 citations
• Synthetic vs Real: Deep Learning on Controlled Noise (2019) — 3 citations
• Text as Neural Operator:Image Manipulation by Text Instruction (2020) — 41 citations
• Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels (2019) — 252 citations
• Beyond Actions: Discriminative Models for Contextual Group Activities (2010) — 163 citations