Fabrizio Falchi
Computer Vision and Pattern Recognition · 2009–2020
A researcher in the Science corpus: 7 papers; trusts 524 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 126 citations into it; #14,436 of 21,575 by trust here, #11,286 by citations
- Artificial Intelligence — 58 citations into it
- Multimodal Learning — 26 citations into it
- Evaluation & Benchmarks — 17 citations into it
- Natural Language Processing — 10 citations into it
- Media Technology — 5 citations into it
- Radiology, Nuclear Medicine and Imaging — 5 citations into it
Whom Fabrizio Falchi trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Yann LeCun
- Alex Krizhevsky
- Geoffrey E. Hinton
- Ross B. Girshick
- Yoshua Bengio
- Andrew Zisserman
- Shaoqing Ren
- Ilya Sutskever
- Diederik P. Kingma
Who trusts Fabrizio Falchi overall
Papers from Fabrizio Falchi's perspective
Ordered by how strongly the researchers Fabrizio Falchi trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- Fine-Grained Visual Textual Alignment for Cross-Modal Retrieval Using Transformer Encoders (2020) — 169 citations
- Deep learning for decentralized parking lot occupancy detection (2017) — 341 citations
- Virtual to Real Adaptation of Pedestrian Detectors (2020) — 38 citations
- Learning Pedestrian Detection from Virtual Worlds (2019) — 29 citations
- Counting Vehicles with Deep Learning in Onboard UAV Imagery (2019) — 47 citations
- Counting Vehicles with Cameras (2018) — 23 citations
- CoPhIR: a Test Collection for Content-Based Image Retrieval (2009) — 178 citations