A. del Bimbo

Computer Vision and Pattern Recognition · 2013–2021

A researcher in the Science corpus: 13 papers; trusts 874 researchers and is trusted by 42 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 245 citations into it; #4,641 of 21,575 by trust here, #4,137 by citations
• Artificial Intelligence — 117 citations into it; #24,440 of 35,345 by trust here, #23,077 by citations
• Representation & Self-Supervised Learning — 38 citations into it
• Model Architectures — 27 citations into it
• Human-Computer Interaction — 26 citations into it; #1,829 of 2,253 by trust here, #896 by citations
• Biomedical Engineering — 21 citations into it; #8,377 of 10,734 by trust here, #5,917 by citations
• Evaluation & Benchmarks — 19 citations into it
• Optimization & Training — 19 citations into it

Whom A. del Bimbo trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. David G. Lowe
4. Kaiming He
5. Yann LeCun
6. Diederik P. Kingma
7. Yoshua Bengio
8. Karen Simonyan
9. Ross B. Girshick
10. Andrew Zisserman

Who trusts A. del Bimbo overall

1. Rahaf Aljundi
2. Liliana Lo Presti
3. Raviteja Vemulapalli
4. Federico Pernici
5. Fei Han
6. Adnan Al Alwani
7. Jacopo Cavazza

Papers from A. del Bimbo's perspective

Ordered by how strongly the researchers A. del Bimbo trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Deep Generative Adversarial Compression Artifact Removal (2017) — 229 citations
• Person Re-Identification by Iterative Re-Weighted Sparse Ranking (2015) — 321 citations
• Recognizing Actions from Depth Cameras as Weakly Aligned Multi-part Bag-of-Poses (2013) — 252 citations
• Dictionary Learning Based 3D Morphable Model Construction for Face Recognition with Varying Expression and Pose (2015) — 48 citations
• Space-Time Pose Representation for 3D Human Action Recognition (2013) — 72 citations
• Combined shape analysis of human poses and motion units for action segmentation and recognition (2015) — 19 citations
• Regular Polytope Networks (2021) — 35 citations
• Class-incremental Learning with Pre-allocated Fixed Classifiers (2020) — 44 citations
• Deepfake Video Detection through Optical Flow Based CNN (2019) — 372 citations
• Unsupervised incremental learning of deep descriptors from video streams (2017) — 12 citations
• Memory Based Online Learning of Deep Representations from Video Streams (2017) — 31 citations
• Human Action Recognition by Shape Analysis of Motion Trajectories on Riemannian Manifold (2014)
• Copy-move forgery detection and localization by means of robust clustering with J-Linkage (2013) — 299 citations