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Sören Pirk

4 papers hereh-index 3661 citations6 works total

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

author position
  • middle author3
  • last author1

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

fields
  • cs.CV4
same name
  • Sören Pirk — 8 papers
  • Sören Pirk — 5 papers
  • Sören Pirk — 2 papers
  • Sören Pirk — 1 paper, h 6

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182022
most citedUnsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics

23 citations · 23 across the 2 of their papers we have counts for

collaborators

4 papers

cs.CV2022

Instance Segmentation with Cross-Modal Consistency

Alex Zihao Zhu, Vincent Casser, Reza Mahjourian +2

Segmenting object instances is a key task in machine perception, with safety-critical applications in robotics and autonomous driving. We introduce a novel approach to instance seg…

cs.CV2020

Taskology: Utilizing Task Relations at Scale

Yao Lu, Sören Pirk, Jan Dlabal +6

Many computer vision tasks address the problem of scene understanding and are naturally interrelated e.g. object classification, detection, scene segmentation, depth estimation, et…

cs.CV2019★ 23 cited

Unsupervised Monocular Depth and Ego-motion Learning with Structure and Semantics

Vincent Casser, Soeren Pirk, Reza Mahjourian +1

We present an approach which takes advantage of both structure and semantics for unsupervised monocular learning of depth and ego-motion. More specifically, we model the motion of…

cs.CV2018

Depth Prediction Without the Sensors: Leveraging Structure for Unsupervised Learning from Monocular Videos

Vincent Casser, Soeren Pirk, Reza Mahjourian +1

Learning to predict scene depth from RGB inputs is a challenging task both for indoor and outdoor robot navigation. In this work we address unsupervised learning of scene depth and…

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