Publications related to Anaglyph 3D

Joint Learning of Semantic Alignment and Object Landmark Detection

Convolutional neural networks (CNNs) based approaches for semantic alignment and object landmark detection have improved their performance significantly. Current efforts for the two tasks focus on addressing the lack of massive training data through weakly ...

IEEE2019

Modeling and Analysis of a Direct Time-of-Flight Sensor Architecture for LiDAR Applications

Edoardo Charbon, Chunmin Zhang, Preethi Padmanabhan

Direct time-of-flight (DTOF) is a prominent depth sensing method in light detection and ranging (LiDAR) applications. Single-photon avalanche diode (SPAD) arrays integrated in DTOF sensors have demonstrated excellent ranging and 3D imaging capabilities, ma ...

2019

Towards Modelling of Visual Saliency in Point Clouds for Immersive Applications

Touradj Ebrahimi, Evangelos Alexiou, Peisen Xu

Modelling human visual attention is of great importance in the field of computer vision and has been widely explored for 3D imaging. Yet, in the absence of ground truth data, it is unclear whether such predictions are in alignment with the actual human vie ...

2019

SUBDIVIDE AND CONQUER Active Contours and Surfaces for Biomedical Image Segmentation

Anaïs Laure Marie-Thérèse Badoual

Ongoing advances in imaging techniques create new demands regarding the analysis of images in medicine and biology. Image segmentation is a key step of many image analysis pipelines and its proper execution is a particularly challenging task. This thesis i ...

EPFL2019

On the first JND and break in presence of 360-degree content

Pascal Frossard, Roberto Gerson De Albuquerque Azevedo

Unlike traditional planar 2D visual content, immersive 360-degree images and videos undergo particular processing steps and are intended to be consumed via head-mounted displays (HMDs). To get a deeper understanding on the perception of 360-degree visual d ...

ACM Press2019

Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching.

François Fleuret, Anton Ivanov, Stepan Tulyakov

End-to-end deep-learning networks recently demonstrated extremely good performance for stereo matching. However, existing networks are difficult to use for practical applications since (1) they are memory-hungry and unable to process even modest-size image ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

Compressive Multiplexing of Ultrasound Signals

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Marcel Arditi, Adrien Georges Jean Besson

High-quality 3D ultrasound (US) imaging requires dense matrix-array probes with thousands of elements and necessitates an unrealistic number of coaxial cables to connect such probes to back-end systems. To address this issue, many techniques have been deve ...

IEEE2018

Compressive Multiplexing of Ultrasound Signals

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Marcel Arditi, Adrien Besson

High-quality 3D ultrasound (US) imaging requires dense matrix-array probes with thousands of elements and necessitates an unrealistic number of coaxial cables to connect such probes to back-end systems. To address this issue, many techniques have been deve ...

IEEE2018

Flexible Single-Photon Image Sensors, CMOS Circuits for Biological Sensing and Processing

Edoardo Charbon

Photon-counting imaging technology has applications in many fields such as fluorescence lifetime imaging microscopy (FLIM), time-resolved Raman spectroscopy, 3D imaging, and even space communications. The requirement to detect single photons with picosecon ...

Springer International Publishing2018

Impact of Visualisation Strategy for Subjective Quality Assessment of Point Clouds

Touradj Ebrahimi, Evangelos Alexiou

Point clouds have recently emerged as a promising and practical solution to code 3D visual information for immersive applications. Among other challenges, objective and subjective quality assessments are still open problems for this type of visual data rep ...

2018

Anaglyph 3D

Joint Learning of Semantic Alignment and Object Landmark Detection

Modeling and Analysis of a Direct Time-of-Flight Sensor Architecture for LiDAR Applications

Towards Modelling of Visual Saliency in Point Clouds for Immersive Applications

SUBDIVIDE AND CONQUER Active Contours and Surfaces for Biomedical Image Segmentation

On the first JND and break in presence of 360-degree content

Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching.

Compressive Multiplexing of Ultrasound Signals

Compressive Multiplexing of Ultrasound Signals

Flexible Single-Photon Image Sensors, CMOS Circuits for Biological Sensing and Processing

Impact of Visualisation Strategy for Subjective Quality Assessment of Point Clouds

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SUBDIVIDE AND CONQUER Active Contours and Surfaces for Biomedical Image Segmentation

Joint Learning of Semantic Alignment and Object Landmark Detection

Modeling and Analysis of a Direct Time-of-Flight Sensor Architecture for LiDAR Applications

Towards Modelling of Visual Saliency in Point Clouds for Immersive Applications

On the first JND and break in presence of 360-degree content

Practical Deep Stereo (PDS): Toward applications-friendly deep stereo matching.

Compressive Multiplexing of Ultrasound Signals

Compressive Multiplexing of Ultrasound Signals

Impact of Visualisation Strategy for Subjective Quality Assessment of Point Clouds

Flexible Single-Photon Image Sensors, CMOS Circuits for Biological Sensing and Processing