298 citations · 608 across the 16 of their papers we have counts for
7 papers · 1 filter
Iterative Deep Learning for Network Topology Extraction
Carles Ventura, Jordi Pont-Tuset, Sergi Caelles +2
This paper tackles the task of estimating the topology of filamentary networks such as retinal vessels and road networks. Building on top of a global model that performs a dense se…
Detection-aided liver lesion segmentation using deep learning
Miriam Bellver, Kevis-Kokitsi Maninis, Jordi Pont-Tuset +3
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…
Deep Extreme Cut: From Extreme Points to Object Segmentation
Kevis-Kokitsi Maninis, Sergi Caelles, Jordi Pont-Tuset +1
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. We do s…
Video Object Segmentation Without Temporal Information
Kevis-Kokitsi Maninis, Sergi Caelles, Yuhua Chen +4
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 fra…
Semantically-Guided Video Object Segmentation
Sergi Caelles, Yuhua Chen, Jordi Pont-Tuset +1
This paper tackles the problem of semi-supervised video object segmentation, that is, segmenting an object in a sequence given its mask in the first frame. One of the main challeng…
The 2017 DAVIS Challenge on Video Object Segmentation
Jordi Pont-Tuset, Federico Perazzi, Sergi Caelles +3
We present the 2017 DAVIS Challenge on Video Object Segmentation, a public dataset, benchmark, and competition specifically designed for the task of video object segmentation. Foll…