Zobrazeno 1 - 10
of 22 798
pro vyhledávání: '"Yong Jin"'
Autor:
Jiao, Xianhe, Lv, Chenlei, Zhao, Junli, Yi, Ran, Wen, Yu-Hui, Pan, Zhenkuan, Wu, Zhongke, Liu, Yong-jin
For large-scale point cloud processing, resampling takes the important role of controlling the point number and density while keeping the geometric consistency. % in related tasks. However, current methods cannot balance such different requirements.
Externí odkaz:
http://arxiv.org/abs/2412.09177
We introduce AlphaTablets, a novel and generic representation of 3D planes that features continuous 3D surface and precise boundary delineation. By representing 3D planes as rectangles with alpha channels, AlphaTablets combine the advantages of curre
Externí odkaz:
http://arxiv.org/abs/2411.19950
Autor:
He, Yuze, Zhou, Yanning, Zhao, Wang, Wu, Zhongkai, Xiao, Kaiwen, Yang, Wei, Liu, Yong-Jin, Han, Xiao
We present StdGEN, an innovative pipeline for generating semantically decomposed high-quality 3D characters from single images, enabling broad applications in virtual reality, gaming, and filmmaking, etc. Unlike previous methods which struggle with l
Externí odkaz:
http://arxiv.org/abs/2411.05738
Autor:
Zhao, Wang, Liu, Jiachen, Zhang, Sheng, Li, Yishu, Chen, Sili, Huang, Sharon X, Liu, Yong-Jin, Guo, Hengkai
This paper presents a generalizable 3D plane detection and reconstruction framework named MonoPlane. Unlike previous robust estimator-based works (which require multiple images or RGB-D input) and learning-based works (which suffer from domain shift)
Externí odkaz:
http://arxiv.org/abs/2411.01226
Reconstructing accurate 3D surfaces for street-view scenarios is crucial for applications such as digital entertainment and autonomous driving simulation. However, existing street-view datasets, including KITTI, Waymo, and nuScenes, only offer noisy
Externí odkaz:
http://arxiv.org/abs/2410.21739
Classifier-Free Guidance (CFG), which combines the conditional and unconditional score functions with two coefficients summing to one, serves as a practical technique for diffusion model sampling. Theoretically, however, denoising with CFG cannot be
Externí odkaz:
http://arxiv.org/abs/2410.18737
Autor:
Lin, Matthieu, Sheng, Jenny, Zhao, Andrew, Wang, Shenzhi, Yue, Yang, Wu, Yiran, Liu, Huan, Liu, Jun, Huang, Gao, Liu, Yong-Jin
In a compound AI system, components such as an LLM call, a retriever, a code interpreter, or tools are interconnected. The system's behavior is primarily driven by parameters such as instructions or tool definitions. Recent advancements enable end-to
Externí odkaz:
http://arxiv.org/abs/2410.16392
Autor:
Liu, Huan, Yang, Shusen, Zhang, Yuzhe, Wang, Mengze, Gong, Fanyu, Xie, Chengxi, Liu, Guanjian, Liu, Zejun, Liu, Yong-Jin, Lu, Bao-Liang, Zhang, Dalin
EEG-based emotion recognition (EER) has gained significant attention due to its potential for understanding and analyzing human emotions. While recent advancements in deep learning techniques have substantially improved EER, the field lacks a convinc
Externí odkaz:
http://arxiv.org/abs/2410.09767
Autor:
Ye, Sheng, He, Yuze, Lin, Matthieu, Sheng, Jenny, Fan, Ruoyu, Han, Yiheng, Hu, Yubin, Yi, Ran, Wen, Yu-Hui, Liu, Yong-Jin, Wang, Wenping
Neural implicit representations have revolutionized dense multi-view surface reconstruction, yet their performance significantly diminishes with sparse input views. A few pioneering works have sought to tackle the challenge of sparse-view reconstruct
Externí odkaz:
http://arxiv.org/abs/2409.05474
Autor:
Gu, Lipeng, Wei, Mingqiang, Yan, Xuefeng, Zhu, Dingkun, Zhao, Wei, Xie, Haoran, Liu, Yong-Jin
Multi-modal 3D multi-object tracking (MOT) typically necessitates extensive computational costs of deep neural networks (DNNs) to extract multi-modal representations. In this paper, we propose an intriguing question: May we learn from multiple modali
Externí odkaz:
http://arxiv.org/abs/2409.00618