Ankush Gupta
Computer Vision and Pattern Recognition · 2012–2023
A researcher in the Science corpus: 9 papers; trusts 1,140 researchers and is trusted by 706 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 347 citations into it; #1,616 of 21,575 by trust here, #3,191 by citations
- Artificial Intelligence — 135 citations into it; #17,913 of 35,345 by trust here, #12,580 by citations
- Representation & Self-Supervised Learning — 67 citations into it
- Evaluation & Benchmarks — 42 citations into it
- Aerospace Engineering — 40 citations into it
- Generative Models — 33 citations into it
- Media Technology — 28 citations into it; #1,583 of 3,621 by trust here, #2,033 by citations
- Model Architectures — 26 citations into it
Whom Ankush Gupta trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Ross B. Girshick
- Alex Krizhevsky
- Karen Simonyan
- Andrew Zisserman
- Kaiming He
- Diederik P. Kingma
- Yoshua Bengio
- Yann LeCun
- Ilya Sutskever
Who trusts Ankush Gupta overall
- Minghui Liao
- Baoguang Shi
- Xiang Bai
- Tong He
- C. V. Jawahar
- Pengyuan Lyu
- Sergey I. Nikolenko
- Hui Li
- Chengquan Zhang
- Chunhua Shen
Papers from Ankush Gupta's perspective
Ordered by how strongly the researchers Ankush Gupta 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)
- 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
- Synthetic Data for Text Localisation in Natural Images (2016) — 1,563 citations
- Unsupervised Learning of Object Keypoints for Perception and Control (2019) — 218 citations
- CrossTransformers: spatially-aware few-shot transfer (2020) — 412 citations
- Choosing Linguistics over Vision to Describe Images (2012) — 139 citations
- TAP-Vid: A Benchmark for Tracking Any Point in a Video (2022) — 317 citations
- Unsupervised Learning of Object Landmarks through Conditional Image Generation (2018) — 271 citations
- TAPIR: Tracking Any Point with per-frame Initialization and temporal Refinement (2023) — 336 citations
- Perception Test: A Diagnostic Benchmark for Multimodal Video Models (2023) — 350 citations
- A case study of trajectory transfer through non-rigid registration for a simplified suturing scenario (2013) — 101 citations