189 citations · 237 across the 9 of their papers we have counts for
5 papers · 1 filter
Zoom-to-Inpaint: Image Inpainting with High-Frequency Details
Soo Ye Kim, Kfir Aberman, Nori Kanazawa +6
Although deep learning has enabled a huge leap forward in image inpainting, current methods are often unable to synthesize realistic high-frequency details. In this paper, we propo…
How to Train Neural Networks for Flare Removal
Yicheng Wu, Qiurui He, Tianfan Xue +4
When a camera is pointed at a strong light source, the resulting photograph may contain lens flare artifacts. Flares appear in a wide variety of patterns (halos, streaks, color ble…
Learned Dual-View Reflection Removal
Simon Niklaus, Xuaner Cecilia Zhang, Jonathan T. Barron +4
Traditional reflection removal algorithms either use a single image as input, which suffers from intrinsic ambiguities, or use multiple images from a moving camera, which is inconv…
Learning to Autofocus
Charles Herrmann, Richard Strong Bowen, Neal Wadhwa +4
Autofocus is an important task for digital cameras, yet current approaches often exhibit poor performance. We propose a learning-based approach to this problem, and provide a reali…
DuNet: Learning Depth Estimation from Dual-Cameras and Dual-Pixels
Yinda Zhang, Neal Wadhwa, Sergio Orts-Escolano +3
Computational stereo has reached a high level of accuracy, but degrades in the presence of occlusions, repeated textures, and correspondence errors along edges. We present a novel…