The Synthesizability of Texture Examples
By Dengxin Dai, Hayko Riemenschneider, Luc Van Gool. 2014
45 citations recorded by the source corpus.
Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Graphics and Computer-Aided Design
- Ning Xu
- Petr Kellnhofer
- Jiaya Jia
- Wojciech Matusik
- Xiaoyong Shen
- Scott D. Cohen
- Brian L. Price
- Changil Kim
In Computer Vision and Pattern Recognition
- Brian L. Price
- Scott D. Cohen
- Luc Van Gool
- Ming-Hsuan Yang
- Jiaya Jia
- Xiaoyong Shen
- Ning Xu
- Jiashi Feng
Citations in the corpus
- FocalClick: Towards Practical Interactive Image Segmentation (2022, neutral): “‘Synthetic’ data uses the datasets of [8,26,43].”
- Getting to 99% Accuracy in Interactive Segmentation (2020, methodology): “The background images come from MS-COCO [41] and ETHZ Synthesizability [43] datasets.”
- Towards real-time photorealistic 3D holography with deep neural networks (2021, background): “…a scene by randomly sampling 200–250 triangle meshes with repetition from a pool of over 50 meshes and assigning each mesh a random texture from a pool of over 60,000 textures from publicly available texture synthesis datasets 44,45 with augmentation (see Methods for more rendering details).”
- Wide-Context Semantic Image Extrapolation (2019, methodology): “1) 128 × 128 → 256 × 256 (used for CelebA-HQ, ETHZ Synthesizability, and CUB200).”