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of 3 911
pro vyhledávání: '"Tan , Ping"'
We aim to address sparse-view reconstruction of a 3D scene by leveraging priors from large-scale vision models. While recent advancements such as 3D Gaussian Splatting (3DGS) have demonstrated remarkable successes in 3D reconstruction, these methods
Externí odkaz:
http://arxiv.org/abs/2409.03456
With polarized and angle-resolved Raman spectroscopy studies on single two-dimensional layered perovskites (2DLP) flakes with different ammonium molecules as organic cations, in 2020 we revealed the very rich phonon spectra in the low-frequency regim
Externí odkaz:
http://arxiv.org/abs/2408.09383
Autor:
Wang, Yinhuai, Zhao, Qihan, Yu, Runyi, Zeng, Ailing, Lin, Jing, Luo, Zhengyi, Tsui, Hok Wai, Yu, Jiwen, Li, Xiu, Chen, Qifeng, Zhang, Jian, Zhang, Lei, Tan, Ping
Mastering basketball skills such as diverse layups and dribbling involves complex interactions with the ball and requires real-time adjustments. Traditional reinforcement learning methods for interaction skills rely on labor-intensive, manually desig
Externí odkaz:
http://arxiv.org/abs/2408.15270
Large-scale multi-session LiDAR mapping is essential for a wide range of applications, including surveying, autonomous driving, crowdsourced mapping, and multi-agent navigation. However, existing approaches often struggle with data redundancy, robust
Externí odkaz:
http://arxiv.org/abs/2408.03723
Neural implicit surface reconstruction has become a new trend in reconstructing a detailed 3D shape from images. In previous methods, however, the 3D scene is only encoded by the MLPs which do not have an explicit 3D structure. To better represent 3D
Externí odkaz:
http://arxiv.org/abs/2408.01677
Autor:
Chen, Suyi, Xu, Hao, Li, Haipeng, Luo, Kunming, Liu, Guanghui, Fu, Chi-Wing, Tan, Ping, Liu, Shuaicheng
Data plays a crucial role in training learning-based methods for 3D point cloud registration. However, the real-world dataset is expensive to build, while rendering-based synthetic data suffers from domain gaps. In this work, we present PointRegGPT,
Externí odkaz:
http://arxiv.org/abs/2407.14054
Visual loop closure detection is an important module in visual simultaneous localization and mapping (SLAM), which associates current camera observation with previously visited places. Loop closures correct drifts in trajectory estimation to build a
Externí odkaz:
http://arxiv.org/abs/2407.11736
Large-scale multi-session LiDAR mapping is crucial for various applications but still faces significant challenges in data redundancy, memory consumption, and efficiency. This paper presents MS-Mapping, a novel multi-session LiDAR mapping system that
Externí odkaz:
http://arxiv.org/abs/2406.02096
Gaussian Splatting (GS) has proven to be highly effective in novel view synthesis, achieving high-quality and real-time rendering. However, its potential for reconstructing detailed 3D shapes has not been fully explored. Existing methods often suffer
Externí odkaz:
http://arxiv.org/abs/2406.01467
We present a novel generative 3D modeling system, coined CraftsMan, which can generate high-fidelity 3D geometries with highly varied shapes, regular mesh topologies, and detailed surfaces, and, notably, allows for refining the geometry in an interac
Externí odkaz:
http://arxiv.org/abs/2405.14979