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Barbara Roessle

4 papers here

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

author position
  • first author1
  • middle author1
  • last author2

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

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  • cs.CV4
ORCID 0009-0004-7866-7785

identity via Semantic Scholar / OpenAlex

most citedDense Depth Priors for Neural Radiance Fields from Sparse Input Views

16 citations · 16 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2024

G3DST: Generalizing 3D Style Transfer with Neural Radiance Fields across Scenes and Styles

Adil Meric, Umut Kocasari, Matthias Nießner +1

Neural Radiance Fields (NeRF) have emerged as a powerful tool for creating highly detailed and photorealistic scenes. Existing methods for NeRF-based 3D style transfer need extensi…

cs.CV2024

Robust 3D Gaussian Splatting for Novel View Synthesis in Presence of Distractors

Paul Ungermann, Armin Ettenhofer, Matthias Nießner +1

3D Gaussian Splatting has shown impressive novel view synthesis results; nonetheless, it is vulnerable to dynamic objects polluting the input data of an otherwise static scene, so…

cs.CV2024

MultiDiff: Consistent Novel View Synthesis from a Single Image

Norman Müller, Katja Schwarz, Barbara Roessle +4

We introduce MultiDiff, a novel approach for consistent novel view synthesis of scenes from a single RGB image. The task of synthesizing novel views from a single reference image i…

cs.CV2021★ 16 cited

Dense Depth Priors for Neural Radiance Fields from Sparse Input Views

Barbara Roessle, Jonathan T. Barron, Ben Mildenhall +2

Neural radiance fields (NeRF) encode a scene into a neural representation that enables photo-realistic rendering of novel views. However, a successful reconstruction from RGB image…

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