9 papers · 1 filter
Visual Relocalization from Sparse Views in Aliased and Low-Texture Environments via Novel View Synthesis
Maria Peribañez, Javier Civera, Rudolph Triebel +1
Visual localization becomes extremely challenging in planetary-like terrains characterized by low texture, perceptual aliasing, harsh illumination, and sparse, weakly overlapping v…
TAPNext++: What's Next for Tracking Any Point (TAP)?
Sebastian Jung, Artem Zholus, Martin Sundermeyer +6
Tracking-Any-Point (TAP) models aim to track any point through a video which is a crucial task in AR/XR and robotics applications. The recently introduced TAPNext approach proposes…
Finding NeMO: A Geometry-Aware Representation of Template Views for Few-Shot Perception
Sebastian Jung, Leonard Klüpfel, Rudolph Triebel +1
We present Neural Memory Object (NeMO), a novel object-centric representation that can be used to detect, segment and estimate the 6DoF pose of objects unseen during training using…
The S3LI Vulcano Dataset: A Dataset for Multi-Modal SLAM in Unstructured Planetary Environments
Riccardo Giubilato, Marcus Gerhard Müller, Marco Sewtz +3
We release the S3LI Vulcano dataset, a multi-modal dataset towards development and benchmarking of Simultaneous Localization and Mapping (SLAM) and place recognition algorithms tha…
Multi-modal Loop Closure Detection with Foundation Models in Severely Unstructured Environments
Laura Alejandra Encinar Gonzalez, John Folkesson, Rudolph Triebel +1
Robust loop closure detection is a critical component of Simultaneous Localization and Mapping (SLAM) algorithms in GNSS-denied environments, such as in the context of planetary ex…
Making the Flow Glow -- Robot Perception under Severe Lighting Conditions using Normalizing Flow Gradients
Simon Kristoffersson Lind, Rudolph Triebel, Volker Krüger
Modern robotic perception is highly dependent on neural networks. It is well known that neural network-based perception can be unreliable in real-world deployment, especially in di…