Zobrazeno 1 - 10
of 727
pro vyhledávání: '"Bao Hujun"'
Autor:
Shen, Yichen, Li, Yijin, Chen, Shuo, Li, Guanglin, Huang, Zhaoyang, Bao, Hujun, Cui, Zhaopeng, Zhang, Guofeng
Feature tracking is crucial for, structure from motion (SFM), simultaneous localization and mapping (SLAM), object tracking and various computer vision tasks. Event cameras, known for their high temporal resolution and ability to capture asynchronous
Externí odkaz:
http://arxiv.org/abs/2409.17981
Autor:
Zhai, Hongjia, Zhang, Xiyu, Zhao, Boming, Li, Hai, He, Yijia, Cui, Zhaopeng, Bao, Hujun, Zhang, Guofeng
Visual localization plays an important role in the applications of Augmented Reality (AR), which enable AR devices to obtain their 6-DoF pose in the pre-build map in order to render virtual content in real scenes. However, most existing approaches ca
Externí odkaz:
http://arxiv.org/abs/2409.14067
Autor:
Shen, Zehong, Pi, Huaijin, Xia, Yan, Cen, Zhi, Peng, Sida, Hu, Zechen, Bao, Hujun, Hu, Ruizhen, Zhou, Xiaowei
We present a novel method for recovering world-grounded human motion from monocular video. The main challenge lies in the ambiguity of defining the world coordinate system, which varies between sequences. Previous approaches attempt to alleviate this
Externí odkaz:
http://arxiv.org/abs/2409.06662
Neural implicit reconstruction via volume rendering has demonstrated its effectiveness in recovering dense 3D surfaces. However, it is non-trivial to simultaneously recover meticulous geometry and preserve smoothness across regions with differing cha
Externí odkaz:
http://arxiv.org/abs/2408.12598
In recent years, the paradigm of neural implicit representations has gained substantial attention in the field of Simultaneous Localization and Mapping (SLAM). However, a notable gap exists in the existing approaches when it comes to scene understand
Externí odkaz:
http://arxiv.org/abs/2407.20853
Autor:
Chen, Danpeng, Li, Hai, Ye, Weicai, Wang, Yifan, Xie, Weijian, Zhai, Shangjin, Wang, Nan, Liu, Haomin, Bao, Hujun, Zhang, Guofeng
Recently, 3D Gaussian Splatting (3DGS) has attracted widespread attention due to its high-quality rendering, and ultra-fast training and rendering speed. However, due to the unstructured and irregular nature of Gaussian point clouds, it is difficult
Externí odkaz:
http://arxiv.org/abs/2406.06521
Autor:
Zhao, Boming, Li, Yuan, Sun, Ziyu, Zeng, Lin, Shen, Yujun, Ma, Rui, Zhang, Yinda, Bao, Hujun, Cui, Zhaopeng
Forecasting future scenarios in dynamic environments is essential for intelligent decision-making and navigation, a challenge yet to be fully realized in computer vision and robotics. Traditional approaches like video prediction and novel-view synthe
Externí odkaz:
http://arxiv.org/abs/2405.19745
Low-Light Video Enhancement (LLVE) seeks to restore dynamic and static scenes plagued by severe invisibility and noise. One critical aspect is formulating a consistency constraint specifically for temporal-spatial illumination and appearance enhanced
Externí odkaz:
http://arxiv.org/abs/2405.15660
Autor:
Dong, Wenqi, Yang, Bangbang, Ma, Lin, Liu, Xiao, Cui, Liyuan, Bao, Hujun, Ma, Yuewen, Cui, Zhaopeng
As humans, we aspire to create media content that is both freely willed and readily controlled. Thanks to the prominent development of generative techniques, we now can easily utilize 2D diffusion methods to synthesize images controlled by raw sketch
Externí odkaz:
http://arxiv.org/abs/2405.08054
Autor:
Cen, Zhi, Pi, Huaijin, Peng, Sida, Shen, Zehong, Yang, Minghui, Zhu, Shuai, Bao, Hujun, Zhou, Xiaowei
Generating human motions from textual descriptions has gained growing research interest due to its wide range of applications. However, only a few works consider human-scene interactions together with text conditions, which is crucial for visual and
Externí odkaz:
http://arxiv.org/abs/2405.07784