Syed Waqas Zamir

Computer Vision and Pattern Recognition · 2019–2026

A researcher in the Science corpus: 12 papers; trusts 1,502 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 842 citations into it; #5,280 of 21,575 by trust here, #2,814 by citations
• Artificial Intelligence — 387 citations into it
• Media Technology — 213 citations into it; #1,020 of 3,621 by trust here, #529 by citations
• Model Architectures — 161 citations into it; #2,206 of 2,278 by trust here, #776 by citations
• Radiology, Nuclear Medicine and Imaging — 80 citations into it
• Evaluation & Benchmarks — 55 citations into it
• Representation & Self-Supervised Learning — 47 citations into it
• Computational Mechanics — 43 citations into it

Whom Syed Waqas Zamir 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. Ross B. Girshick
6. Yoshua Bengio
7. Yann LeCun
8. Ilya Sutskever
9. Karen Simonyan
10. Andrew Zisserman

Who trusts Syed Waqas Zamir overall

1. Liangyu Chen
2. Jie Xiao
3. Jing Lin
4. Zhendong Wang
5. Aditya Arora
6. Salman Hameed Khan
7. Chong Mou
8. Yulun Zhang
9. Xiang Chen
10. Xiaojie Chu

Papers from Syed Waqas Zamir's perspective

Ordered by how strongly the researchers Syed Waqas Zamir 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Gradient-based learning applied to document recognition
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Transformers in Vision: A Survey (2021) — 3,683 citations
• Restormer: Efficient Transformer for High-Resolution Image Restoration (2021) — 4,193 citations
• Multi-Stage Progressive Image Restoration (2021) — 2,207 citations
• Learning Enriched Features for Real Image Restoration and Enhancement (2020) — 989 citations
• iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images (2019) — 507 citations
• CycleISP: Real Image Restoration via Improved Data Synthesis (2020) — 446 citations
• EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications (2022) — 374 citations
• Learning Enriched Features for Fast Image Restoration and Enhancement (2022) — 623 citations
• AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results (2020) — 43 citations
• Transformers in Medical Imaging: A Survey (2022) — 1,206 citations
• AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages (2026)
• PromptIR: Prompting for All-in-One Image Restoration (2023) — 351 citations