Videos

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Adaboost and SVM for object detection Thumbnail

Adaboost and SVM for object detection

Presenter
  • Alan Yuille
August 2, 2013
IPAM
New variational approaches in vision Thumbnail

New variational approaches in vision

Presenter
  • Anand Rangarajan
August 2, 2013
IPAM
Gaussian Processes (II) Thumbnail

Gaussian Processes (II)

Presenter
  • Raquel Urtasun
August 2, 2013
IPAM
Gaussian Processes (I) Thumbnail

Gaussian Processes (I)

Presenter
  • Raquel Urtasun
August 2, 2013
IPAM
Lambertian model of reflectance II: harmonic analysis Thumbnail

Lambertian model of reflectance II: harmonic analysis

Presenter
  • Ronen Basri
August 1, 2013
IPAM
Tutorial on Optimal Mass Transport Theory for Computer Vision Thumbnail

Tutorial on Optimal Mass Transport Theory for Computer Vision

Presenter
  • David Gu
August 1, 2013
IPAM
Lambertian model of reflectance I: shape from shading and photometric stereo Thumbnail

Lambertian model of reflectance I: shape from shading and photometric stereo

Presenter
  • Ronen Basri
August 1, 2013
IPAM
Tutorial on Surface Ricci Flow for Shape Registration and Analysis Thumbnail

Tutorial on Surface Ricci Flow for Shape Registration and Analysis

Presenter
  • David Gu
August 1, 2013
IPAM
Tutorial on Conformal Geometry for Computer Vision Thumbnail

Tutorial on Conformal Geometry for Computer Vision

Presenter
  • David Gu
August 1, 2013
IPAM
20Q for Fast face detection, micro-surgical tool tracking and electron microscopy Thumbnail

20Q for Fast face detection, micro-surgical tool tracking and electron microscopy

Presenter
  • Bruno Jedynak
July 31, 2013
IPAM
Game of Twenty Questions with noisy answers. A paradigm for Human and Computer Vision. Information Theory. Sequential acquisition of information Thumbnail

Game of Twenty Questions with noisy answers. A paradigm for Human and Computer Vision. Information Theory. Sequential acquisition of information

Presenter
  • Bruno Jedynak
July 31, 2013
IPAM
Introduction to Information Theory for Vision Thumbnail

Introduction to Information Theory for Vision

Presenter
  • Ying Nian Wu
July 31, 2013
IPAM