Zobrazeno 1 - 10
of 241
pro vyhledávání: '"Stamminger, Marc"'
Recent advancements in point cloud compression have primarily emphasized geometry compression while comparatively fewer efforts have been dedicated to attribute compression. This study introduces an end-to-end learned dynamic lossy attribute coding a
Externí odkaz:
http://arxiv.org/abs/2408.10665
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 an unordered set of posed images captured by a monocular camera and se
Externí odkaz:
http://arxiv.org/abs/2408.06190
Contactless hand pose estimation requires sensors that provide precise spatial information and low computational complexity for real-time processing. Unlike vision-based systems, radar offers lighting independence and direct motion assessments. Yet,
Externí odkaz:
http://arxiv.org/abs/2406.13464
Autor:
Hahlbohm, Florian, Franke, Linus, Kappel, Moritz, Castillo, Susana, Stamminger, Marc, Magnor, Marcus
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 models, or discrete point cloud proxies, we propose a hybrid scene repr
Externí odkaz:
http://arxiv.org/abs/2403.16862
Autor:
Wirth, Vanessa, Bräunig, Johanna, Khouri, Danti, Gutsche, Florian, Vossiek, Martin, Weyrich, Tim, Stamminger, Marc
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 applications, due to the challenges that arise from mutual sensor calibration in
Externí odkaz:
http://arxiv.org/abs/2403.10981
Point-based radiance field rendering has demonstrated impressive results for novel view synthesis, offering a compelling blend of rendering quality and computational efficiency. However, also latest approaches in this domain are not without their sho
Externí odkaz:
http://arxiv.org/abs/2401.06003
Autor:
Meyer, Lukas, Erich, Floris, Yoshiyasu, Yusuke, Stamminger, Marc, Ando, Noriaki, Domae, Yukiyasu
We introduce Physically Enhanced Gaussian Splatting Simulation System (PEGASUS) for 6DOF object pose dataset generation, a versatile dataset generator based on 3D Gaussian Splatting. Environment and object representations can be easily obtained using
Externí odkaz:
http://arxiv.org/abs/2401.02281
In the last few years, deep neural networks opened the doors for big advances in novel view synthesis. Many of these approaches are based on a (coarse) proxy geometry obtained by structure from motion algorithms. Small deficiencies in this proxy can
Externí odkaz:
http://arxiv.org/abs/2311.04634
Autor:
Herglotz, Christian, Müller, David, Weinlich, Andreas, Bauer, Frank, Ortner, Michael, Stamminger, Marc, Kaup, André
Publikováno v:
Proc. 2018 IEEE International Symposium on Multimedia (ISM)
This paper shows that motion vectors representing the true motion of an object in a scene can be exploited to improve the encoding process of computer generated video sequences. Therefore, a set of sequences is presented for which the true motion vec
Externí odkaz:
http://arxiv.org/abs/2309.06945
Autor:
Bräunig, Johanna, Schüßler, Christian, Wirth, Vanessa, Stamminger, Marc, Ullmann, Ingrid, Vossiek, Martin
With the increasing popularity of human-computer interaction applications, there is also growing interest in generating sufficiently large and diverse data sets for automatic radar-based recognition of hand poses and gestures. Radar simulations are a
Externí odkaz:
http://arxiv.org/abs/2307.15412