61 citations · 119 across the 5 of their papers we have counts for
5 papers · 1 filter
A Dense Material Segmentation Dataset for Indoor and Outdoor Scene Parsing
Paul Upchurch, Ransen Niu
A key algorithm for understanding the world is material segmentation, which assigns a label (metal, glass, etc.) to each pixel. We find that a model trained on existing data underp…
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…
Deep Feature Interpolation for Image Content Changes
Paul Upchurch, Jacob Gardner, Geoff Pleiss +4
We propose Deep Feature Interpolation (DFI), a new data-driven baseline for automatic high-resolution image transformation. As the name suggests, it relies only on simple linear in…
From A to Z: Supervised Transfer of Style and Content Using Deep Neural Network Generators
Paul Upchurch, Noah Snavely, Kavita Bala
We propose a new neural network architecture for solving single-image analogies - the generation of an entire set of stylistically similar images from just a single input image. So…
Material Recognition in the Wild with the Materials in Context Database
Sean Bell, Paul Upchurch, Noah Snavely +1
Recognizing materials in real-world images is a challenging task. Real-world materials have rich surface texture, geometry, lighting conditions, and clutter, which combine to make…