3 papers
cs.CV2024
G3DST: Generalizing 3D Style Transfer with Neural Radiance Fields across Scenes and Styles
Adil Meric, Umut Kocasari, Matthias NieÃner +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 NieÃner +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…