robots.princeton.edu

Princeton Vision & Robotics Group

3D Deep Learning for Object Recognition in Amazon Picking Challenge. Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images. DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving. Princeton Robot Wanderer learns by exploring the environment curiously with a powerful GPU. 3D ShapeNets: A Deep Representation for Volumetric Shapes. Next Best View Selection for Active Object Recognition on a Robot Platform. A minimalist GPU-only N-dimensional ConvNet framework. Focusing on ...

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Princeton Vision & Robotics Group | robots.princeton.edu Reviews

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3D Deep Learning for Object Recognition in Amazon Picking Challenge. Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images. DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving. Princeton Robot Wanderer learns by exploring the environment curiously with a powerful GPU. 3D ShapeNets: A Deep Representation for Volumetric Shapes. Next Best View Selection for Active Object Recognition on a Robot Platform. A minimalist GPU-only N-dimensional ConvNet framework. Focusing on ...

<META> KEYWORDS

1 scene understanding database

2 image based facade modeling

3 scene viewpoint recognition

4 mission

5 sponsor our research

6 autonomous driving

7 and augmented reality

8 news

9 with team mit

10 deep sliding shapes

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scene understanding database,image based facade modeling,scene viewpoint recognition,mission,sponsor our research,autonomous driving,and augmented reality,news,with team mit,deep sliding shapes,marvin,our deepdriving,and places,to dream deeply,magazine

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Princeton Vision & Robotics Group | robots.princeton.edu Reviews

https://robots.princeton.edu

3D Deep Learning for Object Recognition in Amazon Picking Challenge. Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images. DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving. Princeton Robot Wanderer learns by exploring the environment curiously with a powerful GPU. 3D ShapeNets: A Deep Representation for Volumetric Shapes. Next Best View Selection for Active Object Recognition on a Robot Platform. A minimalist GPU-only N-dimensional ConvNet framework. Focusing on ...

INTERNAL PAGES

robots.princeton.edu

1

Image-based Facade Modeling

http://robots.princeton.edu/projects/2008/TOG_facade

J Xiao, T. Fang, P. Tan, P. Zhao, E. Ofek, and L. Quan. ACM Transaction on Graphics (TOG), Volume 27, Number 5. Proceedings of ACM SIGGRAPH Asia 2008. Image selected for Back Cover of ToG. Video is selected for Papers Preview.

2

Reconstructing the World's Museums

http://robots.princeton.edu/projects/2012/museum

Reconstructing the World's Museums. ECCV 2012 Best Student Paper Award. And Google Research Excellent Papers Award. Jianxiong Xiao and Yasutaka Furukawa. Reconstructing the World's Museums. International Journal of Computer Vision (IJCV). Jianxiong Xiao and Yasutaka Furukawa. Reconstructing the World's Museums. Proceedings of the 12th European Conference on Computer Vision (ECCV2012). Oral presentation at the main conference: Powerpoint PPTX slides (781MB). And PDF slides (44MB). And PDF slides (93MB).

3

Image-based Street-side City Modeling

http://robots.princeton.edu/projects/2009/TOG

Image-based Street-side City Modeling. J Xiao, T. Fang, P. Zhao, M. Lhuillier, and L. Quan. Image-based Street-side City Modeling. Proceedings of ACM SIGGRAPH Asia 2009. ACM Transaction on Graphics (TOG), Volume 28, Number 5. This code is to render a Mesh given a 3x4 camera matrix with an image resolution. This is a program for packing texture for rectangles into a big image. This is a code to decompose a 3x4 camera matrix into intrinsic and extrinsic camera paramaters.

4

Recognizing Scene Viewpoint using Panoramic Place Representation

http://robots.princeton.edu/projects/2012/SUN360

Recognizing Scene Viewpoint using Panoramic Place Representation. J Xiao, K. A. Ehinger, A. Oliva and A. Torralba. Recognizing Scene Viewpoint using Panoramic Place Representation. Proceedings of 25th IEEE Conference on Computer Vision and Pattern Recognition, 2012. Short Fast-forward Introduction ( Download. Full Length Video ( Download. Example Results on Panorama.pdf. This file contains more examples of result visualization on our panorama dataset. It is an extension of Figure 8 in the paper. To downl...

5

Localizing 3D Cuboids in Single-view Images

http://robots.princeton.edu/projects/2012/SUNprimitive

Localizing 3D Cuboids in Single-view Images. Given a single-view input image, our goal is to detect the 2D corner locations of the cuboids depicted in the image. With the output part locations we can subsequently recover information about the camera and 3D shape via camera resectioning. J Xiao, B. C. Russell, and A. Torralba. Localizing 3D Cuboids in Single-view Images. Advances in Neural Information Processing Systems 25 (NIPS2012). Pyramid annotation on single-view RGB images. Run "compile" in Matlab.

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3D Deep Learning for Object Recognition in Amazon Picking Challenge. Deep Sliding Shapes for Amodal 3D Object Detection in RGB-D Images. DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving. Princeton Robot Wanderer learns by exploring the environment curiously with a powerful GPU. 3D ShapeNets: A Deep Representation for Volumetric Shapes. Next Best View Selection for Active Object Recognition on a Robot Platform. A minimalist GPU-only N-dimensional ConvNet framework. Focusing on ...

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