Jia Xue

I am a PhD student in Rutgers University, advised by Professor Kristin Dana. My research interest is machine learning and computer vision.

Our GTOS project website is finished, you can download it here. To download material classification database here You can find the label and train/test split here



Differential Angular Imaging for Material Recognition

Jia Xue, Hang Zhang, Kristin Dana, Ko Nishino
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
arXiv | code | project


Deep TEN: Texture Encoding Network

Hang Zhang, Jia Xue, Kristin Dana
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017
arXiv | code


This project develops the first material camera, or MatCam, that outputs a per-pixel label of object material and its properties that can be used in visual computing tasks. In the everyday real world there are a vast number of materials that are useful to discern including concrete, metal, plastic, velvet, satin, water layer on asphalt, carpet, tile, wood, and marble. A device for identifying materials has important implications in developing new technologies. For example, a mobile robot may use a MatCam to determine whether the terrain is grass, gravel, pavement, or snow in order to optimize mechanical control. In e-commerce, the material composition of objects can be tagged by a MatCam for advertising and inventory. The potential applications are limitless in areas such as robotics, digital architecture, human-computer interaction, intelligent vehicles and advanced manufacturing. Furthermore, material maps have foundational importance in nearly all vision algorithms including segmentation, feature matching, scene recognition, image-based rendering, context-based search, and object recognition and motion estimation. The camera brings material recognition to the broader scientific and engineering communities, in a similar way that depth cameras are currently used in many fields outside of computer vision.

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