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20232025
most citedVR-Splatting: Foveated Radiance Field Rendering via 3D Gaussian Splatting and Neural Points

25 citations · 42 across the 16 of their papers we have counts for

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Showing 2024Show all

11 papers · 1 filter

eess.IV2024

MAROON: A Dataset for the Joint Characterization of Near-Field High-Resolution Radio-Frequency and Optical Depth Imaging Techniques

Vanessa Wirth, Johanna Bräunig, Nikolai Hofmann +3

Utilizing the complementary strengths of wavelength-specific range or depth sensors is crucial for robust computer-assisted tasks such as autonomous driving. Despite this, there is…

cs.CV2024★ 25 cited

VR-Splatting: Foveated Radiance Field Rendering via 3D Gaussian Splatting and Neural Points

Linus Franke, Laura Fink, Marc Stamminger

Recent advances in novel view synthesis have demonstrated impressive results in fast photorealistic scene rendering through differentiable point rendering, either via Gaussian Spla…

cs.GR2024★ 1 cited

Efficient Perspective-Correct 3D Gaussian Splatting Using Hybrid Transparency

Florian Hahlbohm, Fabian Friederichs, Tim Weyrich +6

3D Gaussian Splats (3DGS) have proven a versatile rendering primitive, both for inverse rendering as well as real-time exploration of scenes. In these applications, coherence acros…

cs.CV2024

Refinement of Monocular Depth Maps via Multi-View Differentiable Rendering

Laura Fink, Linus Franke, Bernhard Egger +2

Accurate depth estimation is at the core of many applications in computer graphics, vision, and robotics. Current state-of-the-art monocular depth estimators, trained on extensive…

cs.CV2024

FruitNeRF: A Unified Neural Radiance Field based Fruit Counting Framework

Lukas Meyer, Andreas Gilson, Ute Schmid +1

We introduce FruitNeRF, a unified novel fruit counting framework that leverages state-of-the-art view synthesis methods to count any fruit type directly in 3D. Our framework takes…

eess.IV2024

End-to-end learned Lossy Dynamic Point Cloud Attribute Compression

Dat Thanh Nguyen, Daniel Zieger, Marc Stamminger +1

Recent advancements in point cloud compression have primarily emphasized geometry compression while comparatively fewer efforts have been dedicated to attribute compression. This s…

eess.SP2024

An Efficient yet High-Performance Method for Precise Radar-Based Imaging of Human Hand Poses

Johanna Bräunig, Vanessa Wirth, Marc Stamminger +2

Contactless hand pose estimation requires sensors that provide precise spatial information and low computational complexity for real-time processing. Unlike vision-based systems, r…

cs.CV2024

INPC: Implicit Neural Point Clouds for Radiance Field Rendering

Florian Hahlbohm, Linus Franke, Moritz Kappel +4

We introduce a new approach for reconstruction and novel view synthesis of unbounded real-world scenes. In contrast to previous methods using either volumetric fields, grid-based m…

cs.RO2024★ 1 cited

Automatic Spatial Calibration of Near-Field MIMO Radar With Respect to Optical Depth Sensors

Vanessa Wirth, Johanna Bräunig, Danti Khouri +4

Despite an emerging interest in MIMO radar, the utilization of its complementary strengths in combination with optical depth sensors has so far been limited to far-field applicatio…

cs.CV2024

TRIPS: Trilinear Point Splatting for Real-Time Radiance Field Rendering

Linus Franke, Darius Rückert, Laura Fink +1

Point-based radiance field rendering has demonstrated impressive results for novel view synthesis, offering a compelling blend of rendering quality and computational efficiency. Ho…

cs.CV2024★ 1 cited

PEGASUS: Physically Enhanced Gaussian Splatting Simulation System for 6DoF Object Pose Dataset Generation

Lukas Meyer, Floris Erich, Yusuke Yoshiyasu +3

We introduce Physically Enhanced Gaussian Splatting Simulation System (PEGASUS) for 6DOF object pose dataset generation, a versatile dataset generator based on 3D Gaussian Splattin…