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pro vyhledávání: '"REID, IAN A."'
We propose Hi-SLAM, a semantic 3D Gaussian Splatting SLAM method featuring a novel hierarchical categorical representation, which enables accurate global 3D semantic mapping, scaling-up capability, and explicit semantic label prediction in the 3D wor
Externí odkaz:
http://arxiv.org/abs/2409.12518
Autor:
Lafargue, Raphael, Smith, Luke, Vermet, Franck, Löwe, Mathias, Reid, Ian, Gripon, Vincent, Valmadre, Jack
The predominant method for computing confidence intervals (CI) in few-shot learning (FSL) is based on sampling the tasks with replacement, i.e.\ allowing the same samples to appear in multiple tasks. This makes the CI misleading in that it takes into
Externí odkaz:
http://arxiv.org/abs/2409.02850
Autor:
Doan, Anh-Dzung, Phan, Vu Minh Hieu, Gupta, Surabhi, Wagner, Markus, Chin, Tat-Jun, Reid, Ian
Infrared imaging offers resilience against changing lighting conditions by capturing object temperatures. Yet, in few scenarios, its lack of visual details compared to daytime visible images, poses a significant challenge for human and machine interp
Externí odkaz:
http://arxiv.org/abs/2408.14227
Autor:
Zhang, Zeyu, Liu, Akide, Chen, Qi, Chen, Feng, Reid, Ian, Hartley, Richard, Zhuang, Bohan, Tang, Hao
Text-to-motion generation holds potential for film, gaming, and robotics, yet current methods often prioritize short motion generation, making it challenging to produce long motion sequences effectively: (1) Current methods struggle to handle long mo
Externí odkaz:
http://arxiv.org/abs/2407.10061
The costly and time-consuming annotation process to produce large training sets for modelling semantic LiDAR segmentation methods has motivated the development of semi-supervised learning (SSL) methods. However, such SSL approaches often concentrate
Externí odkaz:
http://arxiv.org/abs/2407.07171
Autor:
Doan, Anh-Dzung, Nguyen, Bach Long, Lim, Terry, Jayawardhana, Madhuka, Gupta, Surabhi, Guettier, Christophe, Reid, Ian, Wagner, Markus, Chin, Tat-Jun
Prior to deployment, an object detector is trained on a dataset compiled from a previous data collection campaign. However, the environment in which the object detector is deployed will invariably evolve, particularly in outdoor settings where change
Externí odkaz:
http://arxiv.org/abs/2407.05607
Autor:
Ma, Xianzheng, Bhalgat, Yash, Smart, Brandon, Chen, Shuai, Li, Xinghui, Ding, Jian, Gu, Jindong, Chen, Dave Zhenyu, Peng, Songyou, Bian, Jia-Wang, Torr, Philip H, Pollefeys, Marc, Nießner, Matthias, Reid, Ian D, Chang, Angel X., Laina, Iro, Prisacariu, Victor Adrian
As large language models (LLMs) evolve, their integration with 3D spatial data (3D-LLMs) has seen rapid progress, offering unprecedented capabilities for understanding and interacting with physical spaces. This survey provides a comprehensive overvie
Externí odkaz:
http://arxiv.org/abs/2405.10255
Autor:
Garg, Sourav, Rana, Krishan, Hosseinzadeh, Mehdi, Mares, Lachlan, Sünderhauf, Niko, Dayoub, Feras, Reid, Ian
Mapping is crucial for spatial reasoning, planning and robot navigation. Existing approaches range from metric, which require precise geometry-based optimization, to purely topological, where image-as-node based graphs lack explicit object-level reas
Externí odkaz:
http://arxiv.org/abs/2405.05792
For a complete comprehension of multi-person scenes, it is essential to go beyond basic tasks like detection and tracking. Higher-level tasks, such as understanding the interactions and social activities among individuals, are also crucial. Progress
Externí odkaz:
http://arxiv.org/abs/2404.05578
Autor:
Le, Duy-Tho, Gou, Chenhui, Datta, Stavya, Shi, Hengcan, Reid, Ian, Cai, Jianfei, Rezatofighi, Hamid
Autonomous robot systems have attracted increasing research attention in recent years, where environment understanding is a crucial step for robot navigation, human-robot interaction, and decision. Real-world robot systems usually collect visual data
Externí odkaz:
http://arxiv.org/abs/2404.01686