activity
20142022
most citedThe Cityscapes Dataset for Semantic Urban Scene Understanding

986 citations · 2.4k across the 21 of their papers we have counts for

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Showing 2016Show all

6 papers · 1 filter

cs.CV2016★ 70 cited

Learning Video Object Segmentation from Static Images

Anna Khoreva, Federico Perazzi, Rodrigo Benenson +2

Inspired by recent advances of deep learning in instance segmentation and object tracking, we introduce video object segmentation problem as a concept of guided instance segmentati…

cs.CV2016★ 23 cited

Faceless Person Recognition; Privacy Implications in Social Media

Seong Joon Oh, Rodrigo Benenson, Mario Fritz +1

As we shift more of our lives into the virtual domain, the volume of data shared on the web keeps increasing and presents a threat to our privacy. This works contributes to the und…

cs.CV2016★ 9 cited

Improved Image Boundaries for Better Video Segmentation

Anna Khoreva, Rodrigo Benenson, Fabio Galasso +2

Graph-based video segmentation methods rely on superpixels as starting point. While most previous work has focused on the construction of the graph edges and weights as well as sol…

cs.CV2016★ 986 cited

The Cityscapes Dataset for Semantic Urban Scene Understanding

Marius Cordts, Mohamed Omran, Sebastian Ramos +6

Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications. Object detection has benefited enormously from large-scale datasets, esp…

cs.CV2016★ 31 cited

Simple Does It: Weakly Supervised Instance and Semantic Segmentation

Anna Khoreva, Rodrigo Benenson, Jan Hosang +2

Semantic labelling and instance segmentation are two tasks that require particularly costly annotations. Starting from weak supervision in the form of bounding box detection annota…

cs.CV2016★ 82 cited

How Far are We from Solving Pedestrian Detection?

Shanshan Zhang, Rodrigo Benenson, Mohamed Omran +2

Encouraged by the recent progress in pedestrian detection, we investigate the gap between current state-of-the-art methods and the "perfect single frame detector". We enable our an…