Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Haene, Christian"'
Autor:
Hema, Vishnu Mani, Aich, Shubhra, Haene, Christian, Bazin, Jean-Charles, de la Torre, Fernando
The advancement in deep implicit modeling and articulated models has significantly enhanced the process of digitizing human figures in 3D from just a single image. While state-of-the-art methods have greatly improved geometric precision, the challeng
Externí odkaz:
http://arxiv.org/abs/2410.09690
Autor:
Sun, Keqiang, Jourabloo, Amin, Bhalodia, Riddhish, Meshry, Moustafa, Rong, Yu, Yang, Zhengyu, Nguyen-Phuoc, Thu, Haene, Christian, Xu, Jiu, Johnson, Sam, Li, Hongsheng, Bouaziz, Sofien
Photo-realistic and controllable 3D avatars are crucial for various applications such as virtual and mixed reality (VR/MR), telepresence, gaming, and film production. Traditional methods for avatar creation often involve time-consuming scanning and r
Externí odkaz:
http://arxiv.org/abs/2408.13674
Autor:
Chen, Yu-Chih, Saha, Avinab, Chapiro, Alexandre, Häne, Christian, Bazin, Jean-Charles, Qiu, Bo, Zanetti, Stefano, Katsavounidis, Ioannis, Bovik, Alan C.
We study the visual quality judgments of human subjects on digital human avatars (sometimes referred to as "holograms" in the parlance of virtual reality [VR] and augmented reality [AR] systems) that have been subjected to distortions. We also study
Externí odkaz:
http://arxiv.org/abs/2408.07041
Autor:
Ma, Wufei, Li, Kai, Jiang, Zhongshi, Meshry, Moustafa, Liu, Qihao, Wang, Huiyu, Häne, Christian, Yuille, Alan
Recent video-text foundation models have demonstrated strong performance on a wide variety of downstream video understanding tasks. Can these video-text models genuinely understand the contents of natural videos? Standard video-text evaluations could
Externí odkaz:
http://arxiv.org/abs/2407.13094
Autor:
Qiu, Di, Zhang, Yinda, Beeler, Thabo, Tankovich, Vladimir, Häne, Christian, Fanello, Sean, Rhemann, Christoph, Escolano, Sergio Orts
We propose CHOSEN, a simple yet flexible, robust and effective multi-view depth refinement framework. It can be employed in any existing multi-view stereo pipeline, with straightforward generalization capability for different multi-view capture syste
Externí odkaz:
http://arxiv.org/abs/2404.02225
Autor:
Xu, Jianjin, Motamed, Saman, Vaddamanu, Praneetha, Wu, Chen Henry, Haene, Christian, Bazin, Jean-Charles, de la Torre, Fernando
Face inpainting is important in various applications, such as photo restoration, image editing, and virtual reality. Despite the significant advances in face generative models, ensuring that a person's unique facial identity is maintained during the
Externí odkaz:
http://arxiv.org/abs/2312.03556
Autor:
Ranade, Siddhant, Lassner, Christoph, Li, Kai, Haene, Christian, Chen, Shen-Chi, Bazin, Jean-Charles, Bouaziz, Sofien
Neural Radiance Fields (NeRFs) encode the radiance in a scene parameterized by the scene's plenoptic function. This is achieved by using an MLP together with a mapping to a higher-dimensional space, and has been proven to capture scenes with a great
Externí odkaz:
http://arxiv.org/abs/2212.03406
Immersive maps such as Google Street View and Bing Streetside provide true-to-life views with a massive collection of panoramas. However, these panoramas are only available at sparse intervals along the path they are taken, resulting in visual discon
Externí odkaz:
http://arxiv.org/abs/2202.08752
Autor:
Chen, Zhang, Zhang, Yinda, Genova, Kyle, Fanello, Sean, Bouaziz, Sofien, Haene, Christian, Du, Ruofei, Keskin, Cem, Funkhouser, Thomas, Tang, Danhang
We introduce Multiresolution Deep Implicit Functions (MDIF), a hierarchical representation that can recover fine geometry detail, while being able to perform global operations such as shape completion. Our model represents a complex 3D shape with a h
Externí odkaz:
http://arxiv.org/abs/2109.05591
Autor:
Tankovich, Vladimir, Häne, Christian, Zhang, Yinda, Kowdle, Adarsh, Fanello, Sean, Bouaziz, Sofien
This paper presents HITNet, a novel neural network architecture for real-time stereo matching. Contrary to many recent neural network approaches that operate on a full cost volume and rely on 3D convolutions, our approach does not explicitly build a
Externí odkaz:
http://arxiv.org/abs/2007.12140