Search Results for author: Fredo Durand

Found 23 papers, 7 papers with code

What You Can Learn by Staring at a Blank Wall

no code implementations ICCV 2021 Prafull Sharma, Miika Aittala, Yoav Y. Schechner, Antonio Torralba, Gregory W. Wornell, William T. Freeman, Fredo Durand

We present a passive non-line-of-sight method that infers the number of people or activity of a person from the observation of a blank wall in an unknown room.

Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering

no code implementations NeurIPS 2021 Vincent Sitzmann, Semon Rezchikov, William T. Freeman, Joshua B. Tenenbaum, Fredo Durand

In this work, we propose a novel neural scene representation, Light Field Networks or LFNs, which represent both geometry and appearance of the underlying 3D scene in a 360-degree, four-dimensional light field parameterized via a neural implicit representation.

Meta-Learning Scene Understanding

On the Capability of CNNs to Generalize to Unseen Category-Viewpoint Combinations

no code implementations1 Jan 2021 Spandan Madan, Timothy Henry, Jamell Arthur Dozier, Helen Ho, Nishchal Bhandari, Tomotake Sasaki, Fredo Durand, Hanspeter Pfister, Xavier Boix

We find that learning category and viewpoint in separate networks compared to a shared one leads to an increase in selectivity and invariance, as separate networks are not forced to preserve information about both category and viewpoint.

Object Recognition Viewpoint Estimation

Computational Mirrors: Blind Inverse Light Transport by Deep Matrix Factorization

1 code implementation NeurIPS 2019 Miika Aittala, Prafull Sharma, Lukas Murmann, Adam B. Yedidia, Gregory W. Wornell, William T. Freeman, Fredo Durand

We recover a video of the motion taking place in a hidden scene by observing changes in indirect illumination in a nearby uncalibrated visible region.

A Dataset of Multi-Illumination Images in the Wild

no code implementations ICCV 2019 Lukas Murmann, Michael Gharbi, Miika Aittala, Fredo Durand

Collections of images under a single, uncontrolled illumination have enabled the rapid advancement of core computer vision tasks like classification, detection, and segmentation.

Image Relighting

Flexible SVBRDF Capture with a Multi-Image Deep Network

1 code implementation27 Jun 2019 Valentin Deschaintre, Miika Aittala, Fredo Durand, George Drettakis, Adrien Bousseau

Empowered by deep learning, recent methods for material capture can estimate a spatially-varying reflectance from a single photograph.

Graphics I.3

Single-Image SVBRDF Capture with a Rendering-Aware Deep Network

1 code implementation23 Oct 2018 Valentin Deschaintre, Miika Aittala, Fredo Durand, George Drettakis, Adrien Bousseau

Texture, highlights, and shading are some of many visual cues that allow humans to perceive material appearance in single pictures.

Graphics I.3

Burst Image Deblurring Using Permutation Invariant Convolutional Neural Networks

no code implementations ECCV 2018 Miika Aittala, Fredo Durand

We propose a neural approach for fusing an arbitrary-length burst of photographs suffering from severe camera shake and noise into a sharp and noise-free image.

Deblurring Image Deblurring +1

Synthetically Trained Icon Proposals for Parsing and Summarizing Infographics

1 code implementation27 Jul 2018 Spandan Madan, Zoya Bylinskii, Matthew Tancik, Adrià Recasens, Kimberli Zhong, Sami Alsheikh, Hanspeter Pfister, Aude Oliva, Fredo Durand

While automatic text extraction works well on infographics, computer vision approaches trained on natural images fail to identify the stand-alone visual elements in infographics, or `icons'.

Synthetic Data Generation

Synthesizing Images of Humans in Unseen Poses

1 code implementation CVPR 2018 Guha Balakrishnan, Amy Zhao, Adrian V. Dalca, Fredo Durand, John Guttag

Given an image of a person and a desired pose, we produce a depiction of that person in that pose, retaining the appearance of both the person and background.

Image Generation

Turning Corners Into Cameras: Principles and Methods

no code implementations ICCV 2017 Katherine L. Bouman, Vickie Ye, Adam B. Yedidia, Fredo Durand, Gregory W. Wornell, Antonio Torralba, William T. Freeman

We show that walls and other obstructions with edges can be exploited as naturally-occurring "cameras" that reveal the hidden scenes beyond them.

Understanding Infographics through Textual and Visual Tag Prediction

1 code implementation26 Sep 2017 Zoya Bylinskii, Sami Alsheikh, Spandan Madan, Adria Recasens, Kimberli Zhong, Hanspeter Pfister, Fredo Durand, Aude Oliva

And second, we use these predicted text tags as a supervisory signal to localize the most diagnostic visual elements from within the infographic i. e. visual hashtags.

BubbleView: an interface for crowdsourcing image importance maps and tracking visual attention

no code implementations16 Feb 2017 Nam Wook Kim, Zoya Bylinskii, Michelle A. Borkin, Krzysztof Z. Gajos, Aude Oliva, Fredo Durand, Hanspeter Pfister

In this paper, we present BubbleView, an alternative methodology for eye tracking using discrete mouse clicks to measure which information people consciously choose to examine.

Eye Tracking

A Video-Based Method for Objectively Rating Ataxia

no code implementations13 Dec 2016 Ronnachai Jaroensri, Amy Zhao, Guha Balakrishnan, Derek Lo, Jeremy Schmahmann, John Guttag, Fredo Durand

The performance of our system is comparable to that of a group of ataxia specialists in terms of mean error and correlation, and our system's predictions were consistently within the range of inter-rater variability.

Optical Flow Estimation Pose Estimation

Reflection Removal Using Ghosting Cues

no code implementations CVPR 2015 YiChang Shih, Dilip Krishnan, Fredo Durand, William T. Freeman

For single-pane windows, ghosting cues arise from shifted reflections on the two surfaces of the glass pane.

Reflection Removal

Visual Vibrometry: Estimating Material Properties From Small Motion in Video

no code implementations CVPR 2015 Abe Davis, Katherine L. Bouman, Justin G. Chen, Michael Rubinstein, Fredo Durand, William T. Freeman

The estimation of material properties is important for scene understanding, with many applications in vision, robotics, and structural engineering.

Scene Understanding

Video Magnification in Presence of Large Motions

no code implementations CVPR 2015 Mohamed Elgharib, Mohamed Hefeeda, Fredo Durand, William T. Freeman

Video magnification reveals subtle variations that would be otherwise invisible to the naked eye.

Detecting Pulse from Head Motions in Video

no code implementations CVPR 2013 Guha Balakrishnan, Fredo Durand, John Guttag

We extract heart rate and beat lengths from videos by measuring subtle head motion caused by the Newtonian reaction to the influx of blood at each beat.

Heart Rate Variability

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