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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
Hierarchical Material Recognition from Local Appearance—0
Shape and Texture Recognition in Large Vision-Language ModelsCode0
Single-image Reflectance and Transmittance Estimation from Any Flatbed Scanner—0
Temporal Binding Foundation Model for Material Property Recognition via Tactile Sequence Perception—0
Chebyshev Attention Depth Permutation Texture Network with Latent Texture Attribute LossCode1
Object-Oriented Material Classification and 3D Clustering for Improved Semantic Perception and Mapping in Mobile RobotsCode0
Integrated Sensing and Communications Framework for 6G Networks—0
Beyond Appearances: Material Segmentation with Embedded Spectral Information from RGB-D imageryCode1
Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic DataCode0
Intelligent Parsing: An Automated Parsing Framework for Extracting Design Semantics from E-commerce Creatives—0
UMat: Uncertainty-Aware Single Image High Resolution Material Capture—0
How Will It Drape Like? Capturing Fabric Mechanics from Depth Images—0
MateRobot: Material Recognition in Wearable Robotics for People with Visual ImpairmentsCode1
One-shot recognition of any material anywhere using contrastive learning with physics-based renderingCode0
A Dense Material Segmentation Dataset for Indoor and Outdoor Scene ParsingCode1
Encoding Spatial Distribution of Convolutional Features for Texture RepresentationCode1
Texture-enhanced Light Field Super-resolution with Spatio-Angular Decomposition KernelsCode0
GLAVNet: Global-Local Audio-Visual Cues for Fine-Grained Material Recognition—0
Unsupervised Super-Resolution of Satellite Imagery for High Fidelity Material Label Transfer—0
The joint role of geometry and illumination on material recognition—0
Stochastic Partial Swap: Enhanced Model Generalization and Interpretability for Fine-Grained RecognitionCode1
Deep Learning for Material recognition: most recent advances and open challenges—0
Multi-Class Zero-Shot Learning for Artistic Material Recognition—0
Probabilistic Surface Friction Estimation Based on Visual and Haptic Measurements—0
Angular Luminance for Material Segmentation—0
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