Mar 2026· arXiv.org· Vol abs/2603.16016· 0 citations· 173 references
Computer ScienceEngineering
TL;DR
FlatLands provides a rigorous testbed for uncertainty-aware indoor mapping and generative completion for embodied navigation and is instantiate the task as an end-to-end monocular RGB-to-floormaps pipeline.
Abstract
A single egocentric image typically captures only a small portion of the floor, yet a complete metric traversability map of the surroundings would better serve applications such as indoor navigation. We introduce FlatLands, a dataset and benchmark for single-view bird's-eye view (BEV) floor completion. The dataset contains 270,575 observations from 17,656 real metric indoor scenes drawn from six existing datasets, with aligned observation, visibility, validity, and ground-truth BEV maps, and the benchmark includes both in- and out-of-distribution evaluation protocols. We compare training-free approaches, deterministic models, ensembles, and stochastic generative models. Finally, we instantiate the task as an end-to-end monocular RGB-to-floormaps pipeline. FlatLands provides a rigorous testbed for uncertainty-aware indoor mapping and generative completion for embodied navigation.
SlugTrails is introduced, a floor plan localization benchmark for large indoor spaces under realistic egocentric sensing, and five representative geometric and learned systems under their native sensing configurations are evaluated, finding that stock checkpoints are near zero on SlugTrails and evidence that floor plan...
NaviScale is proposed for semantic-map-based object navigation (ObjectNav), whose predictor can be trained on pairs of partial and complete semantic maps without reconstructing a complete 3D environment for every training sample.
Chuan-Lin Lan, Yan-Wei Zheng, Yu-Xi Jing et al.· 0 citations
Monocular depth estimation has long stood as a fundamental challenge in computer vision, enabling a wide range of applications including 3D reconstruction, robotics, autonomous driving, and augmented reality. This survey traces the field's evolution from early learning-based methods to the emergence of transformative f...
Muxin Liu, Xiaoyang Lyu, Yang-Tian Sun et al.· 2 citations
Indoor building construction sites are demanding environments for visual SLAM, where variable lighting and repetitive, low-textured structures make the system drift over long trajectories, though structural elements such as walls remain distinguishable despite these conditions. These buildings are constructed according...
Asier Bikandi-Noya, Miguel Fernández-Cortizas, Muhammad Shaheer et al.· 0 citations
Marigold V2 achieves state-of-the-art results when applied to other dense regression tasks, such as surface normals estimation and intrinsic image decomposition, and achieves state-of-the-art results when applied to other dense regression tasks, such as surface normals estimation and intrinsic image decomposition.
Igor Pavlovic, Thiemo Wandel, Anton Obukhov et al.· 1 citation· ⚡1
ESTHER is proposed, a model whose stereo geometry, temporal reasoning, and output representation are designed for wearable egocentric stereo, and shows state-of-the-art accu?racy, superior external generalization, and robustness to the missing views, dropped frames, and lighting and motion blur extremes of real egocen...
Hong-Yu Ma, Hai-Rong Qu, Shi-Qi Zhao et al.· 0 citations
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