Reflection Removal via Realistic Training Data Generation

Youxin Pang, Mengke Yuan, Qiang Fu, Dong Ming Yan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


We present a valid polarization-based reflection contaminated image synthesis method, which can provide adequate, diverse and authentic training dataset. Meanwhile, we enhance the neural network by introducing the reflection information as guidance and utilizing adaptive convolution kernel size to fuse multi-scale information. We demonstrate that the proposed approach achieves convincing improvements over state of the arts.
Original languageEnglish (US)
Title of host publicationACM SIGGRAPH 2020 Posters
ISBN (Print)9781450379731
StatePublished - Aug 15 2020


Dive into the research topics of 'Reflection Removal via Realistic Training Data Generation'. Together they form a unique fingerprint.

Cite this