13 citations · 18 across the 4 of their papers we have counts for
5 papers
Materials In Paintings (MIP): An interdisciplinary dataset for perception, art history, and computer vision
Mitchell J. P. van Zuijlen, Hubert Lin, Kavita Bala +2
A painter is free to modify how components of a natural scene are depicted, which can lead to a perceptually convincing image of the distal world. This signals a major difference b…
Insights From A Large-Scale Database of Material Depictions In Paintings
Hubert Lin, Mitchell Van Zuijlen, Maarten W. A. Wijntjes +2
Deep learning has paved the way for strong recognition systems which are often both trained on and applied to natural images. In this paper, we examine the give-and-take relationsh…
DeepSemanticHPPC: Hypothesis-based Planning over Uncertain Semantic Point Clouds
Yutao Han, Hubert Lin, Jacopo Banfi +2
Planning in unstructured environments is challenging -- it relies on sensing, perception, scene reconstruction, and reasoning about various uncertainties. We propose DeepSemanticHP…
Block Annotation: Better Image Annotation for Semantic Segmentation with Sub-Image Decomposition
Hubert Lin, Paul Upchurch, Kavita Bala
Image datasets with high-quality pixel-level annotations are valuable for semantic segmentation: labelling every pixel in an image ensures that rare classes and small objects are a…
Learning Material-Aware Local Descriptors for 3D Shapes
Hubert Lin, Melinos Averkiou, Evangelos Kalogerakis +5
Material understanding is critical for design, geometric modeling, and analysis of functional objects. We enable material-aware 3D shape analysis by employing a projective convolut…