Material Classification
12 papers with code • 0 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Material Classification
MINC
LabPics
SpectroVision
OpenSurfaces
Latest papers
Thermal Spread Functions (TSF): Physics-guided Material Classification
aniketdashpute/tsf
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CVPR 2023
Our key observation is that the rate of heating and cooling of an object depends on the unique intrinsic properties of the material, namely the emissivity and diffusivity.
One-shot recognition of any material anywhere using contrastive learning with physics-based rendering
The synthetic images were rendered using giant collections of textures, objects, and environments generated by computer graphics artists.
Depth Contrast: Self-Supervised Pretraining on 3DPM Images for Mining Material Classification
prakashchhipa/depth-contrast-self-supervised-method
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This work presents a novel self-supervised representation learning method to learn efficient representations without labels on images from a 3DPM sensor (3-Dimensional Particle Measurement; estimates the particle size distribution of material) utilizing RGB images and depth maps of mining material on the conveyor belt.
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.)
How well does CLIP understand texture?
We investigate how well CLIP understands texture in natural images described by natural language.
SimTreeLS: Simulating aerial and terrestrial laser scans of trees
We present an open source tool, SimTreeLS (Simulated Tree Laser Scans), for generating point clouds which simulate scanning with user-defined sensor, trajectory, tree shape and layout parameters.
Roof material classification from aerial imagery
ZFTurbo/DrivenData-Open-AI-Caribbean-Challenge-2nd-place-solution
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Proposed methods includes: method of converting ImageNet weights of neural networks for using multi-channel images; special set of features of second level models that are used in addition to specific predictions of neural networks; special set of image augmentations that improve training accuracy.
Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging
Healthcare-Robotics/spectrovision
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Finally, we present how a robot can combine this high resolution local sensing with images from the robot's head-mounted camera to achieve accurate material classification over a scene of objects on a table.
Fast classification of small X-ray diffraction datasets using data augmentation and deep neural networks
PV-Lab/autoXRD
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npj Computational Materials 2019
We overcome the scarce data problem intrinsic to novel materials development by coupling a supervised machine learning approach with a model-agnostic, physics-informed data augmentation strategy using simulated data from the Inorganic Crystal Structure Database (ICSD) and experimental data.
Zeroth-Order Stochastic Variance Reduction for Nonconvex Optimization
As application demands for zeroth-order (gradient-free) optimization accelerate, the need for variance reduced and faster converging approaches is also intensifying.
