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Found 6 papers, 2 papers with code
A Dense Material Segmentation Dataset for Indoor and Outdoor Scene Parsing
A key algorithm for understanding the world is material segmentation, which assigns a label (metal, glass, etc.)
Block Annotation: Better Image Annotation for Semantic Segmentation with Sub-Image Decomposition
We propose block sub-image annotation as a replacement for full-image annotation.
Deep Feature Interpolation for Image Content Changes
We propose Deep Feature Interpolation (DFI), a new data-driven baseline for automatic high-resolution image transformation.
From A to Z: Supervised Transfer of Style and Content Using Deep Neural Network Generators
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.
Deep Manifold Traversal: Changing Labels with Convolutional Features
Many tasks in computer vision can be cast as a "label changing" problem, where the goal is to make a semantic change to the appearance of an image or some subject in an image in order to alter the class membership.
Material Recognition in the Wild with the Materials in Context Database
In this paper, we introduce a new, large-scale, open dataset of materials in the wild, the Materials in Context Database (MINC), and combine this dataset with deep learning to achieve material recognition and segmentation of images in the wild.
