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pro vyhledávání: '"Dayoub A"'
Recent research in Vision Language Navigation (VLN) has overlooked the development of agents' inquisitive abilities, which allow them to ask clarifying questions when instructions are incomplete. This paper addresses how agents can recognize "when" t
Externí odkaz:
http://arxiv.org/abs/2411.05831
Autor:
Zhang, Wenbo, Li, Yang, Qiao, Yanyuan, Huang, Siyuan, Liu, Jiajun, Dayoub, Feras, Ma, Xiao, Liu, Lingqiao
Generalist robot manipulation policies (GMPs) have the potential to generalize across a wide range of tasks, devices, and environments. However, existing policies continue to struggle with out-of-distribution scenarios due to the inherent difficulty
Externí odkaz:
http://arxiv.org/abs/2410.01220
Autonomous racing demands safe control of vehicles at their physical limits for extended periods of time, providing insights into advanced vehicle safety systems which increasingly rely on intervention provided by vehicle autonomy. Participation in t
Externí odkaz:
http://arxiv.org/abs/2410.00358
We present a novel method for scene change detection that leverages the robust feature extraction capabilities of a visual foundational model, DINOv2, and integrates full-image cross-attention to address key challenges such as varying lighting, seaso
Externí odkaz:
http://arxiv.org/abs/2409.16850
This paper introduces a novel approach to enhancing cross-view localization, focusing on the fine-grained, sequential localization of street-view images within a single known satellite image patch, a significant departure from traditional one-to-one
Externí odkaz:
http://arxiv.org/abs/2408.15569
For robots to robustly understand and interact with the physical world, it is highly beneficial to have a comprehensive representation - modelling geometry, physics, and visual observations - that informs perception, planning, and control algorithms.
Externí odkaz:
http://arxiv.org/abs/2406.10788
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
Autor:
Clement, Benoit, Dubromel, Marie, Santos, Paulo E., Sammut, Karl, Oppert, Michelle, Dayoub, Feras
Autonomous vessels have emerged as a prominent and accepted solution, particularly in the naval defence sector. However, achieving full autonomy for marine vessels demands the development of robust and reliable control and guidance systems that can h
Externí odkaz:
http://arxiv.org/abs/2404.11882
In this work, we present PoIFusion, a conceptually simple yet effective multi-modal 3D object detection framework to fuse the information of RGB images and LiDAR point clouds at the points of interest (PoIs). Different from the most accurate methods
Externí odkaz:
http://arxiv.org/abs/2403.09212
Deep-learning and large scale language-image training have produced image object detectors that generalise well to diverse environments and semantic classes. However, single-image object detectors trained on internet data are not optimally tailored f
Externí odkaz:
http://arxiv.org/abs/2402.03721