Browse State-of-the-Art › Material Classification
Material Classification
15 papers with code · 0 benchmarks · 5 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
5 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
15 shown of 15 papers with code (65 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
-
21 Jul 2022 2 repositories listedA key algorithm for understanding the world is material segmentation, which assigns a label (metal, glass, etc.)
-
17 May 2019 2 repositories listedWe 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…
-
10 May 2018 2 repositories listedTo explore this, we collected a dataset of spectral measurements from two commercially available spectrometers during which a robotic platform interacted with 50 flat material objects, and we show that a neural network…
-
8 Jul 2024 1 repository listedClassification of different object surface material types can play a significant role in the decision-making algorithms for mobile robots and autonomous vehicles.
-
17 May 2024 1 repository listedIn the realm of computer vision material segmentation of natural scenes represents a challenge driven by the complex and diverse appearances of materials.
-
22 Jan 2024 1 repository listedIn evaluating our methodology, we focus on two distinct tasks: material classification and grasping success prediction.
-
3 Apr 2023 1 repository listedOur 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.
-
1 Dec 2022 1 repository listedThe synthetic images were rendered using giant collections of textures, objects, and environments generated by computer graphics artists.
-
18 Oct 2022 1 repository listedThis 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…
-
22 Mar 2022 1 repository listedWe investigate how well CLIP understands texture in natural images described by natural language.
-
24 Nov 2020 1 repository listedWe 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.
-
23 Apr 2020 1 repository listed Syntology ran 4 of 6 samples · 2 unverified · 6 pointer-only (licence)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…
-
Multimodal Material Classification for Robots using Spectroscopy and High Resolution Texture Imaging2 Apr 2020 1 repository listedFinally, 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.
-
25 May 2018 1 repository listed Syntology ran 2 of 5 samples · 3 unverifiedAs application demands for zeroth-order (gradient-free) optimization accelerate, the need for variance reduced and faster converging approaches is also intensifying.
-
6 Mar 2018 1 repository listedWe evaluated the performance of the system by training it to recognise 32 material types in both indoor and outdoor environments.
Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections