Shyamal Buch
Computer Vision and Pattern Recognition · 2017–2025
A researcher in the Science corpus: 9 papers; trusts 569 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 239 citations into it; #16,508 of 21,575 by trust here, #6,206 by citations
- Artificial Intelligence — 189 citations into it; #31,518 of 35,345 by trust here, #2,301 by citations
- Robotics & Control — 51 citations into it
- Multimodal Learning — 36 citations into it
- Natural Language Processing — 33 citations into it
- Model Architectures — 17 citations into it
- Representation & Self-Supervised Learning — 15 citations into it
- Optimization & Training — 9 citations into it
Whom Shyamal Buch trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ross B. Girshick
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Karen Simonyan
- Andrew Zisserman
Who trusts Shyamal Buch overall
- Phuc Xuan Nguyen
- Tianwei Lin
- Humam Alwassel
- Chen-Lin Zhang
- De-An Huang
- Junbin Xiao
- D'idac Sur'is
- Fabian Caba Heilbron
- Pichao Wang
- Mengmeng Xu
Papers from Shyamal Buch's perspective
Ordered by how strongly the researchers Shyamal Buch trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- 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
- On the Opportunities and Risks of Foundation Models (2021) — 6,923 citations
- SST: Single-Stream Temporal Action Proposals (2017) — 445 citations
- BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments (2021) — 255 citations
- Finding "It": Weakly-Supervised Reference-Aware Visual Grounding in Instructional Videos (2018) — 103 citations
- RubiksNet: Learnable 3D-Shift for Efficient Video Action Recognition (2020) — 73 citations
- iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes (2020) — 246 citations
- Revisiting the “Video” in Video-Language Understanding (2022) — 231 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- iGibson, a Simulation Environment for Interactive Tasks in Large Realistic Scenes (2020) — 57 citations