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cs.CV2022
FSID: Fully Synthetic Image Denoising via Procedural Scene Generation
Gyeongmin Choe, Beibei Du, Seonghyeon Nam +3
For low-level computer vision and image processing ML tasks, training on large datasets is critical for generalization. However, the standard practice of relying on real-world imag…
cs.CV2016
Refining Geometry from Depth Sensors using IR Shading Images
Gyeongmin Choe, Jaesik Park, Yu-Wing Tai +1
We propose a method to refine geometry of 3D meshes from a consumer level depth camera, e.g. Kinect, by exploiting shading cues captured from an infrared (IR) camera. A major benef…
cs.CV2016
Fine-scale Surface Normal Estimation using a Single NIR Image
Youngjin Yoon, Gyeongmin Choe, Namil Kim +2
We present surface normal estimation using a single near infrared (NIR) image. We are focusing on fine-scale surface geometry captured with an uncalibrated light source. To tackle…