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Found 5 papers, 2 papers with code
Scan2Part: Fine-grained and Hierarchical Part-level Understanding of Real-World 3D Scans
We propose Scan2Part, a method to segment individual parts of objects in real-world, noisy indoor RGB-D scans.
Towards Part-Based Understanding of RGB-D Scans
Recent advances in 3D semantic scene understanding have shown impressive progress in 3D instance segmentation, enabling object-level reasoning about 3D scenes; however, a finer-grained understanding is required to enable interactions with objects and their functional understanding.
CAD-Deform: Deformable Fitting of CAD Models to 3D Scans
Shape retrieval and alignment are a promising avenue towards turning 3D scans into lightweight CAD representations that can be used for content creation such as mobile or AR/VR gaming scenarios.
Conformal k-NN Anomaly Detector for Univariate Data Streams
Anomalies in time-series data give essential and often actionable information in many applications.
Conformalized density- and distance-based anomaly detection in time-series data
Anomalies (unusual patterns) in time-series data give essential, and often actionable information in critical situations.
