Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Volino, Marco"'
We present a novel framework to reconstruct complete 3D human shapes from a given target image by leveraging monocular unconstrained images. The objective of this work is to reproduce high-quality details in regions of the reconstructed human body th
Externí odkaz:
http://arxiv.org/abs/2407.10586
Autor:
Yang, Haosen, Zhang, Chenhao, Wang, Wenqing, Volino, Marco, Hilton, Adrian, Zhang, Li, Zhu, Xiatian
Point management is a critical component in optimizing 3D Gaussian Splatting (3DGS) models, as the point initiation (e.g., via structure from motion) is distributionally inappropriate. Typically, the Adaptive Density Control (ADC) algorithm is applie
Externí odkaz:
http://arxiv.org/abs/2406.04251
Autor:
Pesavento, Marco, Xu, Yuanlu, Sarafianos, Nikolaos, Maier, Robert, Wang, Ziyan, Yao, Chun-Han, Volino, Marco, Boyer, Edmond, Hilton, Adrian, Tung, Tony
Recent progress in human shape learning, shows that neural implicit models are effective in generating 3D human surfaces from limited number of views, and even from a single RGB image. However, existing monocular approaches still struggle to recover
Externí odkaz:
http://arxiv.org/abs/2403.10357
3D audio-visual production aims to deliver immersive and interactive experiences to the consumer. Yet, faithfully reproducing real-world 3D scenes remains a challenging task. This is partly due to the lack of available datasets enabling audio-visual
Externí odkaz:
http://arxiv.org/abs/2212.01892
We propose a novel framework to reconstruct super-resolution human shape from a single low-resolution input image. The approach overcomes limitations of existing approaches that reconstruct 3D human shape from a single image, which require high-resol
Externí odkaz:
http://arxiv.org/abs/2208.10738
A common problem in the 4D reconstruction of people from multi-view video is the quality of the captured dynamic texture appearance which depends on both the camera resolution and capture volume. Typically the requirement to frame cameras to capture
Externí odkaz:
http://arxiv.org/abs/2108.13739
This paper proposes a novel Attention-based Multi-Reference Super-resolution network (AMRSR) that, given a low-resolution image, learns to adaptively transfer the most similar texture from multiple reference images to the super-resolution output whil
Externí odkaz:
http://arxiv.org/abs/2108.13697
As audio-visual systems increasingly bring immersive and interactive capabilities into our work and leisure activities, so the need for naturalistic test material grows. New volumetric datasets have captured high-quality 3D video, but accompanying au
Externí odkaz:
http://arxiv.org/abs/2105.00641
Publikováno v:
IEEE VR 2020
Immersive audio-visual perception relies on the spatial integration of both auditory and visual information which are heterogeneous sensing modalities with different fields of reception and spatial resolution. This study investigates the perceived co
Externí odkaz:
http://arxiv.org/abs/2003.06656
Existing techniques for dynamic scene reconstruction from multiple wide-baseline cameras primarily focus on reconstruction in controlled environments, with fixed calibrated cameras and strong prior constraints. This paper introduces a general approac
Externí odkaz:
http://arxiv.org/abs/1907.08195