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researcher

Daniel Cremers

11 papers hereh-index 365 citations11 works total

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

author position
  • middle author7
  • last author4

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CV11
same name
  • Daniel Cremers — 21 papers, h 5
  • Daniel Cremers — 20 papers, h 7
  • Daniel Cremers — 16 papers, h 5
  • Daniel Cremers — 14 papers, h 6
  • Daniel Cremers — 14 papers, h 4
  • Daniel Cremers — 11 papers, h 8

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
20232026
most citedA Perspective on Deep Vision Performance with Standard Image and Video Codecs

4 citations · 6 across the 10 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CV2025

Motion-Refined DINOSAUR for Unsupervised Multi-Object Discovery

Xinrui Gong, Oliver Hahn, Christoph Reich +4

Unsupervised multi-object discovery (MOD) aims to detect and localize distinct object instances in visual scenes without any form of human supervision. Recent approaches leverage o…

cs.CV2025

ControlEvents: Controllable Synthesis of Event Camera Datawith Foundational Prior from Image Diffusion Models

Yixuan Hu, Yuxuan Xue, Simon Klenk +2

In recent years, event cameras have gained significant attention due to their bio-inspired properties, such as high temporal resolution and high dynamic range. However, obtaining l…

cs.CV2025

Feed-Forward SceneDINO for Unsupervised Semantic Scene Completion

Aleksandar Jevtić, Christoph Reich, Felix Wimbauer +4

Semantic scene completion (SSC) aims to infer both the 3D geometry and semantics of a scene from single images. In contrast to prior work on SSC that heavily relies on expensive gr…

cs.CV2025★ 2 cited

Scene-Centric Unsupervised Panoptic Segmentation

Oliver Hahn, Christoph Reich, Nikita Araslanov +3

Unsupervised panoptic segmentation aims to partition an image into semantically meaningful regions and distinct object instances without training on manually annotated data. In con…

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