Zobrazeno 1 - 10
of 863
pro vyhledávání: '"Wang Zhaoqi"'
Autor:
Li, Zehao, Han, Wenwei, Cai, Yujun, Jiang, Hao, Bi, Baolong, Gao, Shuqin, Zhao, Honglong, Wang, Zhaoqi
While 3D Gaussian Splatting enables high-quality real-time rendering, existing Gaussian-based frameworks for 3D semantic segmentation still face significant challenges in boundary recognition accuracy. To address this, we propose a novel 3DGS-based f
Externí odkaz:
http://arxiv.org/abs/2412.00392
Reconstructing textureless areas in MVS poses challenges due to the absence of reliable pixel correspondences within fixed patch. Although certain methods employ patch deformation to expand the receptive field, their patches mistakenly skip depth edg
Externí odkaz:
http://arxiv.org/abs/2407.19323
Computer network anomaly detection and log analysis, as an important topic in the field of network security, has been a key task to ensure network security and system reliability. First, existing network anomaly detection and log analysis methods are
Externí odkaz:
http://arxiv.org/abs/2407.05639
Image anomaly detection is a popular research direction, with many methods emerging in recent years due to rapid advancements in computing. The use of artificial intelligence for image anomaly detection has been widely studied. By analyzing images of
Externí odkaz:
http://arxiv.org/abs/2406.13987
In this paper, we introduce Segmentation-Driven Deformation Multi-View Stereo (SD-MVS), a method that can effectively tackle challenges in 3D reconstruction of textureless areas. We are the first to adopt the Segment Anything Model (SAM) to distingui
Externí odkaz:
http://arxiv.org/abs/2401.06385
Trajectory prediction plays a crucial role in autonomous driving. Existing mainstream research and continuoual learning-based methods all require training on complete datasets, leading to poor prediction accuracy when sudden changes in scenarios occu
Externí odkaz:
http://arxiv.org/abs/2309.05683
The reconstruction of textureless areas has long been a challenging problem in MVS due to lack of reliable pixel correspondences between images. In this paper, we propose the Textureless-aware Segmentation And Correlative Refinement guided Multi-View
Externí odkaz:
http://arxiv.org/abs/2308.09990
Trajectory prediction with uncertainty is a critical and challenging task for autonomous driving. Nowadays, we can easily access sensor data represented in multiple views. However, cross-view consistency has not been evaluated by the existing models,
Externí odkaz:
http://arxiv.org/abs/2308.08764
Multi-view stereo is an important research task in computer vision while still keeping challenging. In recent years, deep learning-based methods have shown superior performance on this task. Cost volume pyramid network-based methods which progressive
Externí odkaz:
http://arxiv.org/abs/2207.12032
Autor:
Zhou, Yan, Wang, Zhaoqi, Zheng, Shirong, Zhou, Li, Dai, Lu, Luo, Hao, Zhang, Zecheng, Sui, Mingxiu
Publikováno v:
In Alexandria Engineering Journal December 2024 108:415-427
