Publications related to DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation

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Deep Feature Factorization for Concept Discovery

Sabine Süsstrunk, Radhakrishna Achanta, Edo Collins

We propose Deep Feature Factorization (DFF), a method capable of localizing similar semantic concepts within an image or a set of images. We use DFF to gain insight into a deep convolutional neural network's learned features, where we detect hierarchical c ...

SpringerLink2018

Geodesic Convolutional Shape Optimization

Pascal Fua, François Fleuret, Pierre Bruno Baqué, Edoardo Remelli

Aerodynamic shape optimization has many industrial applications. Existing methods, however, are so computationally demanding that typical engineering practices are to either simply try a limited number of hand-designed shapes or restrict oneself to shapes ...

2018

Large-Scale Image Segmentation with Convolutional Networks

Pedro Henrique Oliveira Pinheiro

Object recognition is one of the most important problems in computer vision. However, visual recognition poses many challenges when tried to be reproduced by artificial systems. A main challenge is the problem of variability: objects can appear across huge ...

EPFL2017

Large-Scale Image Segmentation with Convolutional Networks

Pedro Henrique Oliveira Pinheiro

Sciences et Techniques de l’Ingénieur (STI)2017

Convolutional Neural Networks for Inverse Problems in Imaging—A Review

Michaël Unser, Kyong Hwan Jin, Michael Thompson McCann

In this article, we review recent uses of convolutional neural networks (CNNs) to solve inverse problems in imaging. It has recently become feasible to train deep CNNs on large databases of images, and they have shown outstanding performance on object clas ...

IEEE2017

Learning to Refine Object Segments

Ronan Collobert, Pedro Henrique Oliveira Pinheiro

Object segmentation requires both object-level information and low-level pixel data. This presents a challenge for feedforward networks: lower layers in convolutional nets capture rich spatial information, while upper layers encode object-level knowledge b ...

Springer2016

A MultiPath Network for Object Detection

Pedro Henrique Oliveira Pinheiro

The recent COCO object detection dataset presents several new challenges for object detection. In particular, it contains objects at a broad range of scales, less prototypical images, and requires more precise localization. To address these challenges, we ...

BMVA Press2016

From Image-level to Pixel-level Labeling with Convolutional Networks

Ronan Collobert, Pedro Henrique Oliveira Pinheiro

We are interested in inferring object segmentation by leveraging only object class information, and by considering only minimal priors on the object segmentation task. This problem could be viewed as a kind of weakly supervised segmentation task, and natur ...

2015

DermoNet: densely linked convolutional neural network for efficient skin lesion segmentation

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Deep Feature Factorization for Concept Discovery

Geodesic Convolutional Shape Optimization

Large-Scale Image Segmentation with Convolutional Networks

Large-Scale Image Segmentation with Convolutional Networks

Webly Supervised Semantic Segmentation

Convolutional Neural Networks for Inverse Problems in Imaging—A Review

Learning to Refine Object Segments

A MultiPath Network for Object Detection

Fast and Robust Segmentation of the Striatum Using Deep Convolutional Neural Networks

From Image-level to Pixel-level Labeling with Convolutional Networks

Large-Scale Image Segmentation with Convolutional Networks

Large-Scale Image Segmentation with Convolutional Networks

Geodesic Convolutional Shape Optimization

Convolutional Neural Networks for Inverse Problems in Imaging—A Review

Deep Feature Factorization for Concept Discovery

Fast and Robust Segmentation of the Striatum Using Deep Convolutional Neural Networks

A MultiPath Network for Object Detection

From Image-level to Pixel-level Labeling with Convolutional Networks

Webly Supervised Semantic Segmentation

Learning to Refine Object Segments