André Susano Pinto
Computer Vision and Pattern Recognition · 2019–2025
A researcher in the Science corpus: 9 papers; trusts 561 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 290 citations into it; #16,381 of 21,575 by trust here, #4,525 by citations
- Artificial Intelligence — 253 citations into it; #26,709 of 35,345 by trust here, #6,157 by citations
- Representation & Self-Supervised Learning — 108 citations into it
- Evaluation & Benchmarks — 65 citations into it
- Generative Models — 51 citations into it
- Model Architectures — 49 citations into it
- Optimization & Training — 31 citations into it
- Media Technology — 26 citations into it
Whom André Susano Pinto trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Alex Krizhevsky
- Geoffrey E. Hinton
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Ross B. Girshick
- Yann LeCun
- Karen Simonyan
- Andrew Zisserman
Who trusts André Susano Pinto overall
Papers from André Susano Pinto's perspective
Ordered by how strongly the researchers André Susano Pinto 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)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Going deeper with convolutions
Their papers
- A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark (2019) — 558 citations
- Scaling Vision with Sparse Mixture of Experts (2021) — 1,110 citations
- UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes (2022) — 84 citations
- Scalable Transfer Learning with Expert Models (2020) — 72 citations
- In-domain representation learning for remote sensing (2019) — 78 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- Gemma 3 Technical Report (2025) — 1,621 citations
- PaliGemma: A versatile 3B VLM for transfer (2024) — 728 citations
- The Visual Task Adaptation Benchmark (2019) — 129 citations