Austin Stone

Orcid: 0000-0003-3175-8810

According to our database1, Austin Stone authored at least 19 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2024
Towards flexible perception with visual memory.
CoRR, 2024

2023
Open-World Object Manipulation using Pre-trained Vision-Language Models.
CoRR, 2023

Scaling Robot Learning with Semantically Imagined Experience.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023


Open-vocabulary Queryable Scene Representations for Real World Planning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Token Turing Machines.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Self-supervised AutoFlow.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Open-World Object Manipulation using Pre-Trained Vision-Language Models.
Proceedings of the Conference on Robot Learning, 2023

2022
Simple Open-Vocabulary Object Detection with Vision Transformers.
CoRR, 2022

Conditional Object-Centric Learning from Video.
Proceedings of the Tenth International Conference on Learning Representations, 2022



2021
The Distracting Control Suite - A Challenging Benchmark for Reinforcement Learning from Pixels.
CoRR, 2021

SMURF: Self-Teaching Multi-Frame Unsupervised RAFT With Full-Image Warping.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Coupling Shared and Tunable Negative Competition Against Winner-Take-All Resource Competition Via CRISPRi Moieties.
Proceedings of the 2021 American Control Conference, 2021

2020
What Matters in Unsupervised Optical Flow.
Proceedings of the Computer Vision - ECCV 2020, 2020

Learning Object-conditioned Exploration using Distributed Soft Actor Critic.
Proceedings of the 4th Conference on Robot Learning, 2020

2019
Towards Object Detection from Motion.
CoRR, 2019

2017
Teaching Compositionality to CNNs.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017


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