Zobrazeno 1 - 10
of 125
pro vyhledávání: '"Ye, Jianbo"'
We present 3DGS-CD, the first 3D Gaussian Splatting (3DGS)-based method for detecting physical object rearrangements in 3D scenes. Our approach estimates 3D object-level changes by comparing two sets of unaligned images taken at different times. Leve
Externí odkaz:
http://arxiv.org/abs/2411.03706
Autor:
Ye, Vickie, Li, Ruilong, Kerr, Justin, Turkulainen, Matias, Yi, Brent, Pan, Zhuoyang, Seiskari, Otto, Ye, Jianbo, Hu, Jeffrey, Tancik, Matthew, Kanazawa, Angjoo
gsplat is an open-source library designed for training and developing Gaussian Splatting methods. It features a front-end with Python bindings compatible with the PyTorch library and a back-end with highly optimized CUDA kernels. gsplat offers numero
Externí odkaz:
http://arxiv.org/abs/2409.06765
Autor:
Lu, Ziqi, Ye, Jianbo, Fei, Xiaohan, Li, Xiaolong, Mo, Jiawei, Swaminathan, Ashwin, Soatto, Stefano
Neural Radiance Field (NeRF), as an implicit 3D scene representation, lacks inherent ability to accommodate changes made to the initial static scene. If objects are reconfigured, it is difficult to update the NeRF to reflect the new state of the scen
Externí odkaz:
http://arxiv.org/abs/2403.11024
Akademický článek
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Humans are arguably innately prepared to comprehend others' emotional expressions from subtle body movements. If robots or computers can be empowered with this capability, a number of robotic applications become possible. Automatically recognizing hu
Externí odkaz:
http://arxiv.org/abs/1808.09568
In this study, we explore capsule networks with dynamic routing for text classification. We propose three strategies to stabilize the dynamic routing process to alleviate the disturbance of some noise capsules which may contain "background" informati
Externí odkaz:
http://arxiv.org/abs/1804.00538
Autor:
Zheng, Xinye, Ye, Jianbo, Chen, Yukun, Wistar, Stephen, Li, Jia, Piedra-Fernández, Jose A., Steinberg, Michael A., Wang, James Z.
Meteorologists use shapes and movements of clouds in satellite images as indicators of several major types of severe storms. Satellite imaginary data are in increasingly higher resolution, both spatially and temporally, making it impossible for human
Externí odkaz:
http://arxiv.org/abs/1802.08937
Model pruning has become a useful technique that improves the computational efficiency of deep learning, making it possible to deploy solutions in resource-limited scenarios. A widely-used practice in relevant work assumes that a smaller-norm paramet
Externí odkaz:
http://arxiv.org/abs/1802.00124
Strict partial order is a mathematical structure commonly seen in relational data. One obstacle to extracting such type of relations at scale is the lack of large-scale labels for building effective data-driven solutions. We develop an active learnin
Externí odkaz:
http://arxiv.org/abs/1801.06481
Movie recommendation systems provide users with ranked lists of movies based on individual's preferences and constraints. Two types of models are commonly used to generate ranking results: long-term models and session-based models. While long-term mo
Externí odkaz:
http://arxiv.org/abs/1712.09059