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Material Recognition

Material recognition focuses on identifying classes, types, states, and properties of materials.

Papers

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Showing 1–25 of 65 papers

TitleStatusHype
Deep TEN: Texture Encoding NetworkCode2
Chebyshev Attention Depth Permutation Texture Network with Latent Texture Attribute LossCode1
Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture ImagingCode1
Encoding Spatial Distribution of Convolutional Features for Texture RepresentationCode1
Differential Viewpoints for Ground Terrain Material RecognitionCode1
Describing Textures in the WildCode1
MateRobot: Material Recognition in Wearable Robotics for People with Visual ImpairmentsCode1
A Dense Material Segmentation Dataset for Indoor and Outdoor Scene ParsingCode1
Beyond Appearances: Material Segmentation with Embedded Spectral Information from RGB-D imageryCode1
Stochastic Partial Swap: Enhanced Model Generalization and Interpretability for Fine-Grained RecognitionCode1
A fully end-to-end deep learning approach for real-time simultaneous 3D reconstruction and material recognition—0
Deep Material Recognition in Light-Fields via Disentanglement of Spatial and Angular Information—0
Geometry-Informed Material Recognition—0
Binary Patterns Encoded Convolutional Neural Networks for Texture Recognition and Remote Sensing Scene Classification—0
Deep Learning for Material recognition: most recent advances and open challenges—0
Integrated Sensing and Communications Framework for 6G Networks—0
A 4D Light-Field Dataset and CNN Architectures for Material Recognition—0
Face Anti-Spoofing with Human Material Perception—0
Fabric Surface Characterization: Assessment of Deep Learning-based Texture Representations Using a Challenging Dataset—0
Deep convolutional filter banks for texture recognition and segmentation—0
Angular Luminance for Material Segmentation—0
Fusion of Convolutional Neural Network and Statistical Features for Texture classification—0
Hierarchical Material Recognition from Local Appearance—0
GLAVNet: Global-Local Audio-Visual Cues for Fine-Grained Material Recognition—0
Differential Angular Imaging for Material Recognition—0
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