Search Results for author: Szymon Rusinkiewicz

Found 19 papers, 6 papers with code

UltraGlove: Hand Pose Estimation with Mems-Ultrasonic Sensors

no code implementations22 Jun 2023 Qiang Zhang, Yuanqiao Lin, Yubin Lin, Szymon Rusinkiewicz

Hand tracking is an important aspect of human-computer interaction and has a wide range of applications in extended reality devices.

Hand Pose Estimation

TidyBot: Personalized Robot Assistance with Large Language Models

1 code implementation9 May 2023 Jimmy Wu, Rika Antonova, Adam Kan, Marion Lepert, Andy Zeng, Shuran Song, Jeannette Bohg, Szymon Rusinkiewicz, Thomas Funkhouser

For a robot to personalize physical assistance effectively, it must learn user preferences that can be generally reapplied to future scenarios.

Self-supervised Neural Articulated Shape and Appearance Models

no code implementations CVPR 2022 Fangyin Wei, Rohan Chabra, Lingni Ma, Christoph Lassner, Michael Zollhöfer, Szymon Rusinkiewicz, Chris Sweeney, Richard Newcombe, Mira Slavcheva

In addition, our representation enables a large variety of applications, such as few-shot reconstruction, the generation of novel articulations, and novel view-synthesis.

Novel View Synthesis

Learning Pneumatic Non-Prehensile Manipulation with a Mobile Blower

1 code implementation5 Apr 2022 Jimmy Wu, Xingyuan Sun, Andy Zeng, Shuran Song, Szymon Rusinkiewicz, Thomas Funkhouser

We investigate pneumatic non-prehensile manipulation (i. e., blowing) as a means of efficiently moving scattered objects into a target receptacle.

Closed-Loop Control of Additive Manufacturing via Reinforcement Learning

no code implementations29 Sep 2021 Michal Piovarci, Michael Foshey, Timothy Erps, Jie Xu, Vahid Babaei, Piotr Didyk, Wojciech Matusik, Szymon Rusinkiewicz, Bernd Bickel

We further show that in combination with reinforcement learning, our model can be used to discover control policies that outperform state-of-the-art controllers.

reinforcement-learning Reinforcement Learning (RL)

Amortized Synthesis of Constrained Configurations Using a Differentiable Surrogate

1 code implementation NeurIPS 2021 Xingyuan Sun, Tianju Xue, Szymon Rusinkiewicz, Ryan P. Adams

We compare our approach to direct optimization of the design using the learned surrogate, and to supervised learning of the synthesis problem.

Physical Simulations

Spatial Intention Maps for Multi-Agent Mobile Manipulation

1 code implementation23 Mar 2021 Jimmy Wu, Xingyuan Sun, Andy Zeng, Shuran Song, Szymon Rusinkiewicz, Thomas Funkhouser

The ability to communicate intention enables decentralized multi-agent robots to collaborate while performing physical tasks.

Learning to Infer Semantic Parameters for 3D Shape Editing

no code implementations9 Nov 2020 Fangyin Wei, Elena Sizikova, Avneesh Sud, Szymon Rusinkiewicz, Thomas Funkhouser

Many applications in 3D shape design and augmentation require the ability to make specific edits to an object's semantic parameters (e. g., the pose of a person's arm or the length of an airplane's wing) while preserving as much existing details as possible.

SymmetryNet: Learning to Predict Reflectional and Rotational Symmetries of 3D Shapes from Single-View RGB-D Images

no code implementations2 Aug 2020 Yifei Shi, Junwen Huang, Hongjia Zhang, Xin Xu, Szymon Rusinkiewicz, Kai Xu

We propose an end-to-end deep neural network which is able to predict both reflectional and rotational symmetries of 3D objects present in the input RGB-D image.

Multi-Task Learning Symmetry Detection

Efficient Spatially Adaptive Convolution and Correlation

no code implementations23 Jun 2020 Thomas W. Mitchel, Benedict Brown, David Koller, Tim Weyrich, Szymon Rusinkiewicz, Michael Kazhdan

Fast methods for convolution and correlation underlie a variety of applications in computer vision and graphics, including efficient filtering, analysis, and simulation.

Spatial Action Maps for Mobile Manipulation

1 code implementation20 Apr 2020 Jimmy Wu, Xingyuan Sun, Andy Zeng, Shuran Song, Johnny Lee, Szymon Rusinkiewicz, Thomas Funkhouser

Typical end-to-end formulations for learning robotic navigation involve predicting a small set of steering command actions (e. g., step forward, turn left, turn right, etc.)

Q-Learning Value prediction

Accelerating Large-Kernel Convolution Using Summed-Area Tables

no code implementations26 Jun 2019 Linguang Zhang, Maciej Halber, Szymon Rusinkiewicz

In this work, we explore using learnable box filters to allow for convolution with arbitrarily large kernel size, while keeping the number of parameters per filter constant.

Pose Estimation

Learning to Detect Features in Texture Images

no code implementations CVPR 2018 Linguang Zhang, Szymon Rusinkiewicz

Local feature detection is a fundamental task in computer vision, and hand-crafted feature detectors such as SIFT have shown success in applications including image-based localization and registration.

Image-Based Localization

High-Precision Localization Using Ground Texture

no code implementations29 Oct 2017 Linguang Zhang, Adam Finkelstein, Szymon Rusinkiewicz

We introduce an image-based global localization system that is accurate to a few millimeters and performs reliable localization both indoors and outside.

Vocal Bursts Intensity Prediction

Wide-Baseline Hair Capture Using Strand-Based Refinement

no code implementations CVPR 2013 Linjie Luo, Cha Zhang, Zhengyou Zhang, Szymon Rusinkiewicz

We propose a novel algorithm to reconstruct the 3D geometry of human hairs in wide-baseline setups using strand-based refinement.

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