82 citations · 228 across the 17 of their papers we have counts for
17 papers
Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Data
Sagi Eppel, Jolina Li, Manuel Drehwald +1
Visual recognition of materials and their states is essential for understanding the physical world, from identifying wet regions on surfaces or stains on fabrics to detecting infec…
MVTrans: Multi-View Perception of Transparent Objects
Yi Ru Wang, Yuchi Zhao, Haoping Xu +4
Transparent object perception is a crucial skill for applications such as robot manipulation in household and laboratory settings. Existing methods utilize RGB-D or stereo inputs t…
One-shot recognition of any material anywhere using contrastive learning with physics-based rendering
Manuel S. Drehwald, Sagi Eppel, Jolina Li +2
Visual recognition of materials and their states is essential for understanding most aspects of the world, from determining whether food is cooked, metal is rusted, or a chemical r…
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network
Mario Krenn, Lorenzo Buffoni, Bruno Coutinho +13
A tool that could suggest new personalized research directions and ideas by taking insights from the scientific literature could significantly accelerate the progress of science. A…
Seeing Glass: Joint Point Cloud and Depth Completion for Transparent Objects
Haoping Xu, Yi Ru Wang, Sagi Eppel +3
The basis of many object manipulation algorithms is RGB-D input. Yet, commodity RGB-D sensors can only provide distorted depth maps for a wide range of transparent objects due ligh…
Predicting 3D shapes, masks, and properties of materials, liquids, and objects inside transparent containers, using the TransProteus CGI dataset
Sagi Eppel, Haoping Xu, Yi Ru Wang +1
We present TransProteus, a dataset, and methods for predicting the 3D structure, masks, and properties of materials, liquids, and objects inside transparent vessels from a single i…