Zobrazeno 1 - 10
of 1 227
pro vyhledávání: '"Xue Nan"'
This paper studies the problem of distribution matching (DM), which is a fundamental machine learning problem seeking to robustly align two probability distributions. Our approach is established on a relaxed formulation, called partial distribution m
Externí odkaz:
http://arxiv.org/abs/2409.10499
The surface tension of partially wetting droplets deforms soft substrates. These deformations are usually localized to a narrow region near the contact line, forming a so-called `elastocapillary ridge.' When a droplet slides along a substrate, the mo
Externí odkaz:
http://arxiv.org/abs/2409.00280
Estimating 3D full-body avatars from AR/VR devices is essential for creating immersive experiences in AR/VR applications. This task is challenging due to the limited input from Head Mounted Devices, which capture only sparse observations from the hea
Externí odkaz:
http://arxiv.org/abs/2405.20786
Learning 3D scene representation from a single-view image is a long-standing fundamental problem in computer vision, with the inherent ambiguity in predicting contents unseen from the input view. Built on the recently proposed 3D Gaussian Splatting (
Externí odkaz:
http://arxiv.org/abs/2405.20310
Autor:
Liu, Xianpeng, Zheng, Ce, Qian, Ming, Xue, Nan, Chen, Chen, Zhang, Zhebin, Li, Chen, Wu, Tianfu
We present Multi-View Attentive Contextualization (MvACon), a simple yet effective method for improving 2D-to-3D feature lifting in query-based multi-view 3D (MV3D) object detection. Despite remarkable progress witnessed in the field of query-based M
Externí odkaz:
http://arxiv.org/abs/2405.12200
Autor:
Xue, Nan, Sun, Yaping, Chen, Zhiyong, Tao, Meixia, Xu, Xiaodong, Qian, Liang, Cui, Shuguang, Zhang, Ping
Large Language Models (LLMs) have achieved significant success in various natural language processing tasks, but how wireless communications can support LLMs has not been extensively studied. In this paper, we propose a wireless distributed LLMs para
Externí odkaz:
http://arxiv.org/abs/2405.03131
Autor:
Zhang, Shangzhan, Peng, Sida, Xu, Tao, Yang, Yuanbo, Chen, Tianrun, Xue, Nan, Shen, Yujun, Bao, Hujun, Hu, Ruizhen, Zhou, Xiaowei
This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing methods that synthesize texture maps, we propose to generate segment-wise procedural material graphs as the appearance representation, which supports high-qua
Externí odkaz:
http://arxiv.org/abs/2404.17569
Autor:
Liu, Zhiheng, Ouyang, Hao, Wang, Qiuyu, Cheng, Ka Leong, Xiao, Jie, Zhu, Kai, Xue, Nan, Liu, Yu, Shen, Yujun, Cao, Yang
3D Gaussians have recently emerged as an efficient representation for novel view synthesis. This work studies its editability with a particular focus on the inpainting task, which aims to supplement an incomplete set of 3D Gaussians with additional p
Externí odkaz:
http://arxiv.org/abs/2404.11613
Autor:
Xiao, Yuxi, Wang, Qianqian, Zhang, Shangzhan, Xue, Nan, Peng, Sida, Shen, Yujun, Zhou, Xiaowei
Recovering dense and long-range pixel motion in videos is a challenging problem. Part of the difficulty arises from the 3D-to-2D projection process, leading to occlusions and discontinuities in the 2D motion domain. While 2D motion can be intricate,
Externí odkaz:
http://arxiv.org/abs/2404.04319
Autor:
Xiao, Yuting, Wang, Xuan, Li, Jiafei, Cai, Hongrui, Fan, Yanbo, Xue, Nan, Yang, Minghui, Shen, Yujun, Gao, Shenghua
This is only a preview version of GauMesh. Recently, primitive-based rendering has been proven to achieve convincing results in solving the problem of modeling and rendering the 3D dynamic scene from 2D images. Despite this, in the context of novel v
Externí odkaz:
http://arxiv.org/abs/2403.11453