davheld.github.io davheld.github.io

davheld.github.io

David Held

I am currently working as a post-doc with Pieter Abbeel. As part of the Berkeley Artificial Intelligence Research Laboratory. My research lies at the intersection of robotics, machine learning, and computer vision. I have applied this idea of learning to understand environmental changes to improve a robot's capabilities in two domains: autonomous driving. And object manipulation. Within autonomous driving. I recently completed my Ph.D. in computer science at Stanford working with Sebastian Thrun. David H...

http://davheld.github.io/

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David Held | davheld.github.io Reviews
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I am currently working as a post-doc with Pieter Abbeel. As part of the Berkeley Artificial Intelligence Research Laboratory. My research lies at the intersection of robotics, machine learning, and computer vision. I have applied this idea of learning to understand environmental changes to improve a robot's capabilities in two domains: autonomous driving. And object manipulation. Within autonomous driving. I recently completed my Ph.D. in computer science at Stanford working with Sebastian Thrun. David H...
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1 about me
2 and silvio savarese
3 awards
4 and sebastian thrun
5 publications
6 project page
7 full paper
8 supplement
9 david held
10 jesse levinson
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about me,and silvio savarese,awards,and sebastian thrun,publications,project page,full paper,supplement,david held,jesse levinson,sebastian thrun,silvio savarese,abstract,bibtex,older work,lynette jones,ian hunter
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David Held | davheld.github.io Reviews

https://davheld.github.io

I am currently working as a post-doc with Pieter Abbeel. As part of the Berkeley Artificial Intelligence Research Laboratory. My research lies at the intersection of robotics, machine learning, and computer vision. I have applied this idea of learning to understand environmental changes to improve a robot's capabilities in two domains: autonomous driving. And object manipulation. Within autonomous driving. I recently completed my Ph.D. in computer science at Stanford working with Sebastian Thrun. David H...

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davheld.github.io davheld.github.io
1

Combining 3D Shape, Color, and Motion for Robust Velocity Estimation

http://davheld.github.io/anytime_tracking.html

Combining 3D Shape, Color, and Motion for Robust Velocity Estimation. Robust Real-Time Tracking Combining 3D Shape, Color, and Motion. David Held, Jesse Levinson, Sebastian Thrun, Silvio Savarese. International Journal of Robotics Research (IJRR), 2015. Combining 3D Shape, Color, and Motion for Robust Anytime Tracking. David Held, Jesse Levinson, Sebastian Thrun, Silvio Savarese. Robotics: Science and Systems (RSS), 2014. Precision Tracking with Sparse 3D and Dense Color 2D Data. Here are some other mode...

2

Probabilistic Framework for Real-time 3D Segmentation using Spatial, Temporal, and Semantic Cues

http://davheld.github.io/GOTURN/GOTURN.html

Learning to Track at 100 FPS with Deep Regression Networks. Learning to Track at 100 FPS with Deep Regression Networks. David Held, Sebastian Thrun, Silvio Savarese. European Conference on Computer Vision (ECCV), 2016 (In press). The C code for the neural-network tracker is available on github here. If you have any further questions about the tracker, please email me at davheld -at- cs -dot- stanford -dot- edu. The performance of GOTURN (including failure cases) can be seen in this video:.

3

Probabilistic Framework for Real-time 3D Segmentation using Spatial, Temporal, and Semantic Cues

http://davheld.github.io/segmentation3D/segmentation3D.html

A Probabilistic Framework for Real-time 3D Segmentation using Spatial, Temporal, and Semantic Cues. Devin Guillory, Brice Rebsamen,. An extended version of the paper with a more detailed derivation of the method can be found here:. The original publication is available here:. A Probabilistic Framework for Real-time 3D Segmentation using Spatial, Temporal, and Semantic Cues. David Held, Devin Guillory, Brice Rebsamen, Sebastian Thrun, Silvio Savarese. Robotics: Science and Systems (RSS), 2016 (In press).

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bair.berkeley.edu bair.berkeley.edu

Berkeley Artificial Intelligence Research Lab

http://bair.berkeley.edu/students.html

Machine learning, Markov decision processes, reinforcement learning, bandit optimization, representation learning. Machine learning, Markov decision processes, reinforcement learning, bandit optimization, representation learning. Adv: Michael I. Jordan. Statistics, Machine Learning, MCMC Methods, Computer Systems. Statistics, Machine Learning, MCMC Methods, Computer Systems. Applying Deep Learning to multi-media applications. Applying Deep Learning to multi-media applications. Online learning, convex opt...

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I am currently working as a post-doc with Pieter Abbeel. As part of the Berkeley Artificial Intelligence Research Laboratory. My research lies at the intersection of robotics, machine learning, and computer vision. I have applied this idea of learning to understand environmental changes to improve a robot's capabilities in two domains: autonomous driving. And object manipulation. Within autonomous driving. I recently completed my Ph.D. in computer science at Stanford working with Sebastian Thrun. David H...

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DAV high energy physicist. Most Recent Entries] [Calendar View]. Below are the 20. Most recent journal entries recorded in davhep. Saturday, May 17th, 2014. Сегодня поговорим про тривиальную, но зачастую. Игнорируемую двойственность понятия "принять решение". Решения могут быть во-первых, эмоционально-волевыми - по установке целей и ценностей, а во-вторых рациональными - по выбору способа достижений цели (поставленной ранее). Monday, May 5th, 2014. Считает, что высшие потребности и стремления человека ни...