This paper proposes a new long-term visual localization method which fuses depth and semantic information in the scene.
Oct 22, 2024 · To solve these problems, this paper proposes a new long-term visual localization method which fuses depth and semantic information in the scene, ...
May 10, 2023 · Detailed results for all conditions ; Learning invariant semantic representation for long-term robust visual localization, 17.6 / 42.1 / 91.3 ...
Learning invariant semantic representation for long-term robust visual localization ... long-term visual place recognition. Yanhai Tan, Peng Ji, Yunzhou ...
Since the intrinsic semantics are invariant to the local appearance changes, this paper proposes to learn semantic-aware local features in order to improve ...
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Since the intrinsic semantics are invariant to the local appearance changes, this paper proposes to learn semantic-aware local features in order to improve ...
Our goal is to jointly learn local and global representa- tions for visual localization. Inspired by the invariance of semantic class labels to viewing ...
Robust visual localization under a wide range of view- ing conditions is a fundamental problem in computer vi- sion. Handling the difficult cases of this ...
Jul 20, 2022 · This paper proposes to learn semantic-aware local features in order to improve robustness of local feature matching for long term localization.
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These methods are scale-invariant and robust to condition change. Hierarchical methods follow a coarse-to- fine localization paradigm [5], [7], [15], [16].