Search Results for author: Kevis-Kokitsi Maninis

Found 19 papers, 13 papers with code

Estimating Generic 3D Room Structures from 2D Annotations

1 code implementation NeurIPS 2023 Denys Rozumnyi, Stefan Popov, Kevis-Kokitsi Maninis, Matthias Nießner, Vittorio Ferrari

Based on these 2D annotations, we automatically reconstruct 3D plane equations for the structural elements and their spatial extent in the scene, and connect adjacent elements at the appropriate contact edges.

Scene Understanding

CAD-Estate: Large-scale CAD Model Annotation in RGB Videos

1 code implementation ICCV 2023 Kevis-Kokitsi Maninis, Stefan Popov, Matthias Nießner, Vittorio Ferrari

We propose a method for annotating videos of complex multi-object scenes with a globally-consistent 3D representation of the objects.

3D Object Reconstruction Object +1

Vid2CAD: CAD Model Alignment using Multi-View Constraints from Videos

1 code implementation8 Dec 2020 Kevis-Kokitsi Maninis, Stefan Popov, Matthias Nießner, Vittorio Ferrari

We address the task of aligning CAD models to a video sequence of a complex scene containing multiple objects.

The 2019 DAVIS Challenge on VOS: Unsupervised Multi-Object Segmentation

no code implementations2 May 2019 Sergi Caelles, Jordi Pont-Tuset, Federico Perazzi, Alberto Montes, Kevis-Kokitsi Maninis, Luc van Gool

We present the 2019 DAVIS Challenge on Video Object Segmentation, the third edition of the DAVIS Challenge series, a public competition designed for the task of Video Object Segmentation (VOS).

Object Segmentation +4

Attentive Single-Tasking of Multiple Tasks

2 code implementations CVPR 2019 Kevis-Kokitsi Maninis, Ilija Radosavovic, Iasonas Kokkinos

In this work we address task interference in universal networks by considering that a network is trained on multiple tasks, but performs one task at a time, an approach we refer to as "single-tasking multiple tasks".

The Liver Tumor Segmentation Benchmark (LiTS)

6 code implementations13 Jan 2019 Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivantik, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C. Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Míriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B. Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Gruen, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John Lowengrub, Jun Ma, Klaus Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yu, Liping Zhang, Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, Bjoern Menze

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018.

Benchmarking Computed Tomography (CT) +3

The 2018 DAVIS Challenge on Video Object Segmentation

no code implementations1 Mar 2018 Sergi Caelles, Alberto Montes, Kevis-Kokitsi Maninis, Yu-Hua Chen, Luc van Gool, Federico Perazzi, Jordi Pont-Tuset

Motivated by the analysis of the results of the 2017 edition, the main track of the competition will be the same than in the previous edition (segmentation given the full mask of the objects in the first frame -- semi-supervised scenario).

Interactive Segmentation Object +4

Iterative Deep Learning for Network Topology Extraction

no code implementations4 Dec 2017 Carles Ventura, Jordi Pont-Tuset, Sergi Caelles, Kevis-Kokitsi Maninis, Luc van Gool

This paper tackles the task of estimating the topology of filamentary networks such as retinal vessels and road networks.

Detection-aided liver lesion segmentation using deep learning

2 code implementations29 Nov 2017 Miriam Bellver, Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Xavier Giro-i-Nieto, Jordi Torres, Luc van Gool

A fully automatic technique for segmenting the liver and localizing its unhealthy tissues is a convenient tool in order to diagnose hepatic diseases and assess the response to the according treatments.

Computed Tomography (CT) Lesion Segmentation +1

Deep Extreme Cut: From Extreme Points to Object Segmentation

2 code implementations CVPR 2018 Kevis-Kokitsi Maninis, Sergi Caelles, Jordi Pont-Tuset, Luc van Gool

This paper explores the use of extreme points in an object (left-most, right-most, top, bottom pixels) as input to obtain precise object segmentation for images and videos.

Instance Segmentation Interactive Segmentation +4

Video Object Segmentation Without Temporal Information

no code implementations18 Sep 2017 Kevis-Kokitsi Maninis, Sergi Caelles, Yu-Hua Chen, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc van Gool

Video Object Segmentation, and video processing in general, has been historically dominated by methods that rely on the temporal consistency and redundancy in consecutive video frames.

Foreground Segmentation Object +6

Convolutional Oriented Boundaries: From Image Segmentation to High-Level Tasks

2 code implementations17 Jan 2017 Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Pablo Arbeláez, Luc van Gool

We present Convolutional Oriented Boundaries (COB), which produces multiscale oriented contours and region hierarchies starting from generic image classification Convolutional Neural Networks (CNNs).

Boundary Detection Contour Detection +7

One-Shot Video Object Segmentation

7 code implementations CVPR 2017 Sergi Caelles, Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Laura Leal-Taixé, Daniel Cremers, Luc van Gool

This paper tackles the task of semi-supervised video object segmentation, i. e., the separation of an object from the background in a video, given the mask of the first frame.

Foreground Segmentation Object +5

Deep Retinal Image Understanding

1 code implementation5 Sep 2016 Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Pablo Arbeláez, Luc van Gool

This paper presents Deep Retinal Image Understanding (DRIU), a unified framework of retinal image analysis that provides both retinal vessel and optic disc segmentation.

General Classification Image Classification +4

Convolutional Oriented Boundaries

1 code implementation9 Aug 2016 Kevis-Kokitsi Maninis, Jordi Pont-Tuset, Pablo Arbeláez, Luc van Gool

We present Convolutional Oriented Boundaries (COB), which produces multiscale oriented contours and region hierarchies starting from generic image classification Convolutional Neural Networks (CNNs).

Contour Detection General Classification +2

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