Publications related to Computational photography

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

EPFL2024

Seeing Photons in Color

Edoardo Charbon, Claudio Bruschini, Paul Mos, Mohit Gupta

Megapixel single-photon avalanche diode (SPAD) arrays have been developed recently, opening up the possibility of deploying SPADs as general-purpose passive cameras for photography and computer vision. However, most previous work on SPADs has been limited ...

ASSOC COMPUTING MACHINERY2023

LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection

Jiancheng Yang, Bo Du, Rui Xu

Convolutional neural networks (CNNs) have been demonstrated to be highly effective in the field of pulmonary nodule detection. However, existing CNN based pulmonary nodule detection methods lack the ability to capture long-range dependencies, which is vita ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

GeoNeRF: Generalizing NeRF with Geometry Priors

François Fleuret

We present GeoNeRF, a generalizable photorealistic novel view synthesis method based on neural radiance fields. Our approach consists of two main stages: a geometry reasoner and a renderer. To render a novel view, the geometry reasoner first constructs cas ...

IEEE COMPUTER SOC2022

NTIRE 2021 Depth Guided Image Relighting Challenge

Sabine Süsstrunk, Majed El Helou, Ruofan Zhou, Radu Timofte

Image relighting is attracting increasing interest due to its various applications. From a research perspective, image relighting can be exploited to conduct both image normalization for domain adaptation, and also for data augmentation. It also has multip ...

IEEE COMPUTER SOC2021

DepthInSpace: Exploitation and Fusion of Multiple Video Frames for Structured-Light Depth Estimation

François Fleuret, Camilla Carta

We present DepthInSpace, a self-supervised deep-learning method for depth estimation using a structured-light camera. The design of this method is motivated by the commercial use case of embedded depth sensors in nowadays smartphones. We first propose to u ...

IEEE2021

Wavelength-Multiplexed Single-Shot Ptychography

Yves Bellouard

We present multi-wavelength single-shot ptychography, a technique which is ideally suited for imaging dynamically evolving plasmas. Through improvements to single-shot ptychography and a novel probe constraint, wavelength-multiplexed single-shot ptychograp ...

IEEE2020

Painting by Numbers: Computational Methods and the History of Art

Leonardo Laurence Impett

This thesis presents a new methodology for computational art history, in the tradition of Distant Reading from literary criticism. This method is based on operationalisation, the transcription of a concept or theory from cultural history into an algorithm. ...

EPFL2020

Quanta burst photography

Edoardo Charbon, Claudio Bruschini, Arin Can Ülkü, Mohit Gupta, Shantanu Gupta

Single-photon avalanche diodes (SPADs) are an emerging sensor technology capable of detecting individual incident photons, and capturing their time-of-arrival with high timing precision. While these sensors were limited to singlepixel or low-resolution dev ...

2020

Contrast measures for predicting perceptual effects of daylight in architectural renderings

Marilyne Andersen, María Lovísa Ámundadóttir, Siobhan Francois Rockcastle

Daylit architecture is perceived as a dynamic luminous composition, yet most existing performance metrics were designed to evaluate natural illumination for its ability to adequately illuminate a two-dimensional task surface and avoid glare-based discomfor ...

SAGE Publications2017

Learning Lightprobes for Mixed Reality Illumination

Pascal Fua, Vincent Lepetit, Kwang Moo Yi

This paper presents the first photometric registration pipeline for Mixed Reality based on high quality illumination estimation by convolutional neural network (CNN) methods. For easy adaptation and deployment of the system, we train the CNN using purely s ...

2017

Tensor low-rank and sparse light field photography

Pierre Vandergheynst, Mahdad Hosseini Kamal

High-quality light field photography has been one of the most difficult challenges in computational photography. Conventional methods either sacrifice resolution, use multiple devices, or require multiple images to be captured. Combining coded image acquis ...

Elsevier2016

Vision-Based Unmanned Aerial Vehicle Detection and Tracking for Sense and Avoid Systems

Pascal Fua, Denis Gillet, Alcherio Martinoli, Vincent Lepetit, Artem Rozantsev, Steven Adriaan Roelofsen, Krishna Raj Sapkota

We propose an approach for on-line detection of small Unmanned Aerial Vehicles (UAVs) and estimation of their relative positions and velocities in the 3D environment from a single moving camera in the context of sense and avoid systems. This problem is cha ...

Ieee2016

Sampling Models in Light Fields

Zhou Xue

What is the actual information contained in light rays filling the 3-D world? Leonardo da Vinci saw the world as an infinite number of radiant pyramids caused by the objects located in it. Nowadays, the radiant pyramid is usually described as a set of ligh ...

EPFL2016

Robust 3D Object Pose Estimation and Tracking from Monocular Images in Industrial Environments

Alberto Crivellaro

Recent advances in Computer Vision are changing our way of living and enabling new applications for both leisure and professional use. Regrettably, in many industrial domains the spread of state-of-the-art technologies is made challenging by the abundance ...

EPFL2016

Encoder-Driven Inpainting Strategy in Multiview Video Compression

Pascal Frossard, Thomas Maugey, Yu Gao

In free viewpoint video systems, where a user has the freedom to select a virtual view from which an observation image of the 3D scene is rendered, the scene is commonly represented by texture and depth images from multiple nearby viewpoints. In such repre ...

Institute of Electrical and Electronics Engineers2016

Exploiting Large Image Sets for Road Scene Parsing

Mathieu Salzmann

There is an increasing interest in exploiting multiple images for scene understanding, with great progress in areas such as cosegmentation and video segmentation. Jointly analyzing the images in a large set offers the opportunity to exploit a greater sourc ...

IEEE Institute of Electrical and Electronics Engineers2016

Shapes from Pixels

Mitra Fatemi

In today's digital world, sampling is at the heart of any signal acquisition device. Imaging devices are ubiquitous examples that capture two-dimensional visual signals and store them as the pixels of discrete images. The main concern is whether and how th ...

EPFL2016

Human perceptions of daylight composition in architecture: a preliminary study to compare quantitative contrast measures with subjective user assessments in HDR renderings

Marilyne Andersen, Siobhan Francois Rockcastle

Humans perceive daylight as a rich and dynamic luminous composition and yet existing performance metrics most often evaluate natural illumination for its ability to adequately illuminate a two-dimensional task surface while avoiding glare-based visual disc ...

2015

Adaptive Sampling for Large Scale Boosting

François Fleuret, Charles Dubout

Classical Boosting algorithms, such as AdaBoost, build a strong classifier without concern for the computational cost. Some applications, in particular in computer vision, may involve millions of training examples and very large feature spaces. In such con ...

2014