Zobrazeno 1 - 10
of 2 481
pro vyhledávání: '"Yan, Pei"'
Autor:
Yu, Xin, Yuan, Ze, Guo, Yuan-Chen, Liu, Ying-Tian, Liu, JianHui, Li, Yangguang, Cao, Yan-Pei, Liang, Ding, Qi, Xiaojuan
Publikováno v:
ACM Transactions on Graphics (TOG) 2024, Volume 43, Issue 6, Article No.: 213, Pages 1-14
While high-quality texture maps are essential for realistic 3D asset rendering, few studies have explored learning directly in the texture space, especially on large-scale datasets. In this work, we depart from the conventional approach of relying on
Externí odkaz:
http://arxiv.org/abs/2411.14740
Autor:
Yang, Yunhan, Huang, Yukun, Guo, Yuan-Chen, Lu, Liangjun, Wu, Xiaoyang, Lam, Edmund Y., Cao, Yan-Pei, Liu, Xihui
3D part segmentation is a crucial and challenging task in 3D perception, playing a vital role in applications such as robotics, 3D generation, and 3D editing. Recent methods harness the powerful Vision Language Models (VLMs) for 2D-to-3D knowledge di
Externí odkaz:
http://arxiv.org/abs/2411.07184
Diffusion models have emerged as a popular method for 3D generation. However, it is still challenging for diffusion models to efficiently generate diverse and high-quality 3D shapes. In this paper, we introduce OctFusion, which can generate 3D shapes
Externí odkaz:
http://arxiv.org/abs/2408.14732
Video representation is a long-standing problem that is crucial for various down-stream tasks, such as tracking,depth prediction,segmentation,view synthesis,and editing. However, current methods either struggle to model complex motions due to the abs
Externí odkaz:
http://arxiv.org/abs/2406.13870
Viewing omnidirectional images (ODIs) in virtual reality (VR) represents a novel form of media that provides immersive experiences for users to navigate and interact with digital content. Nonetheless, this sense of immersion can be greatly compromise
Externí odkaz:
http://arxiv.org/abs/2405.00351
Autor:
Fuente, Asunción, Roueff, Evelyne, Petit, Franck Le, Bourlot, Jacques Le, Bron, Emeric, Wolfire, Mark G., Babb, James F., Yan, Pei-Gen, Onaka, Takashi, Black, John H., Schroetter, Ilane, Van De Putte, Dries, Sidhu, Ameek, Canin, Amélie, Trahin, Boris, Alarcón, Felipe, Chown, Ryan, Kannavou, Olga, Berné, Olivier, Habart, Emilie, Peeters, Els, Goicoechea, Javier R., Zannese, Marion, Meshaka, Raphael, Okada, Yoko, Röllig, Markus, Gal, Romane Le, Sales, Dinalva A., Palumbo, Maria Elisabetta, Baratta, Giuseppe Antonio, Madden, Suzanne C., Neelamkodan, Naslim, Zhang, Ziwei E., Stancil, P. C.
One of the main problems in astrochemistry is determining the amount of sulfur in volatiles and refractories in the interstellar medium. The detection of the main sulfur reservoirs (icy H$_2$S and atomic gas) has been challenging, and estimates are b
Externí odkaz:
http://arxiv.org/abs/2404.09235
Monocular 3D object detection has attracted widespread attention due to its potential to accurately obtain object 3D localization from a single image at a low cost. Depth estimation is an essential but challenging subtask of monocular 3D object detec
Externí odkaz:
http://arxiv.org/abs/2404.03181
The emergence of 3D Gaussian Splatting (3DGS) has greatly accelerated the rendering speed of novel view synthesis. Unlike neural implicit representations like Neural Radiance Fields (NeRF) that represent a 3D scene with position and viewpoint-conditi
Externí odkaz:
http://arxiv.org/abs/2403.11134
Autor:
Tochilkin, Dmitry, Pankratz, David, Liu, Zexiang, Huang, Zixuan, Letts, Adam, Li, Yangguang, Liang, Ding, Laforte, Christian, Jampani, Varun, Cao, Yan-Pei
This technical report introduces TripoSR, a 3D reconstruction model leveraging transformer architecture for fast feed-forward 3D generation, producing 3D mesh from a single image in under 0.5 seconds. Building upon the LRM network architecture, Tripo
Externí odkaz:
http://arxiv.org/abs/2403.02151
In the field of digital content creation, generating high-quality 3D characters from single images is challenging, especially given the complexities of various body poses and the issues of self-occlusion and pose ambiguity. In this paper, we present
Externí odkaz:
http://arxiv.org/abs/2402.17214