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M. Proesmans

4 papers hereh-index 244.6k citations97 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4

identity via Semantic Scholar / OpenAlex

activity
20172020
most citedFast Scene Understanding for Autonomous Driving

49 citations · 49 across the 1 of their papers we have counts for

collaborators

4 papers

cs.CV2020

SCAN: Learning to Classify Images without Labels

Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis +2

Can we automatically group images into semantically meaningful clusters when ground-truth annotations are absent? The task of unsupervised image classification remains an important…

cs.CV2019

Instance Segmentation by Jointly Optimizing Spatial Embeddings and Clustering Bandwidth

Davy Neven, Bert De Brabandere, Marc Proesmans +1

Current state-of-the-art instance segmentation methods are not suited for real-time applications like autonomous driving, which require fast execution times at high accuracy. Altho…

cs.CV2019

End-to-end Lane Detection through Differentiable Least-Squares Fitting

Wouter Van Gansbeke, Bert De Brabandere, Davy Neven +2

Lane detection is typically tackled with a two-step pipeline in which a segmentation mask of the lane markings is predicted first, and a lane line model (like a parabola or spline)…

cs.CV2017★ 49 cited

Fast Scene Understanding for Autonomous Driving

Davy Neven, Bert De Brabandere, Stamatios Georgoulis +2

Most approaches for instance-aware semantic labeling traditionally focus on accuracy. Other aspects like runtime and memory footprint are arguably as important for real-time applic…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.