Concept

Active contour model

Related publications (113)

Rigidity-Aware Detection for 6D Object Pose Estimation

Mathieu Salzmann, Yinlin Hu, Jingyu Li, Rui Song

Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill-suited to handle cluttered scenes, thus producing poor ...

Los Alamitos2023

Gradient-based Methods for Deep Model Interpretability

Suraj Srinivas

In this dissertation, we propose gradient-based methods for characterizing model behaviour for the purposes of knowledge transfer and post-hoc model interpretation. Broadly, gradients capture the variation of some output feature of the model upon unit vari ...

EPFL2021

Impact of the skull contour definition on Leksell Gamma Knife(R)Icon (TM) radiosurgery treatment planning

Constantin Tuleasca

Introduction The Gamma Knife(R)planning software (TMR 10, Elekta Instruments, AB, Sweden) affords two ways of defining the skull volume, the "historical" one using manual measurements (still perform in some centers) and the new one using image-based skull ...

2020

Max-infinitely divisible models and inference for spatial extremes

Emeric Rolland Georges Thibaud, Raphaël Huser

For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max-stable models are inadequate to capture the rate of joint tail decay, and to estimate jo ...

WILEY2020

Inferring Assembly Objects and Sequences from Demonstrations

Mahdi Nobar

Various unsupervised learning algorithms including GMM, Birch, Mean- Shift, K-means and DBSCAN were used to cluster the image and depth sensor data. However, it was not possible to ﬁt the clusters on each objects quite separately in as much as data are too ...

2019

Geometry in active learning for binary and multi-class image segmentation

Pascal Fua, Raphael Sznitman, Ksenia Konyushkova

We propose an active learning approach to image segmentation that exploits geometric priors to speed up and streamline the annotation process. It can be applied for both background foreground and multi-class segmentation tasks in 2D images and 3D image vol ...

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

SROBB: Targeted Perceptual Loss for Single Image Super-Resolution

Jean-Philippe Thiran, Hazim Kemal Ekenel, Mohammad Saeed Rad

By benefiting from perceptual losses, recent studies have improved significantly the performance of the super-resolution task, where a high-resolution image is resolved from its low-resolution counterpart. Although such objective functions generate near-ph ...

IEEE COMPUTER SOC2019

Object Shape Approximation and Contour Adaptive Depth Image Coding for Virtual View Synthesis

Pascal Frossard, Yuan Yuan

A depth image provides partial geometric information of a 3D scene, namely the shapes of physical objects as observed from a particular viewpoint. This information is important when synthesizing images of different virtual camera viewpoints via depth-image ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2018

Personalized Anatomic Eye Model From T1-Weighted Volume Interpolated Gradient Echo Magnetic Resonance Imaging of Patients With Uveal Melanoma

Meritxell Bach Cuadra, Raphael Sznitman, Alessia Pica

Purpose: We present a 3-dimensional patient-specific eye model from magnetic resonance imaging (MRI) for proton therapy treatment planning of uveal melanoma (UM). During MRI acquisition of UM patients, the point fixation can be difficult and, together with ...

ELSEVIER SCIENCE INC2018

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