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20172020
most citedVideo Frame Interpolation via Adaptive Separable Convolution

72 citations · 118 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2020

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…

cs.CV20202 cited

Deep Homography Estimation for Dynamic Scenes

Hoang Le, Feng Liu, Shu Zhang +1

Homography estimation is an important step in many computer vision problems. Recently, deep neural network methods have shown to be favorable for this problem when compared to trad…

cs.CV2020

Softmax Splatting for Video Frame Interpolation

Simon Niklaus, Feng Liu

Differentiable image sampling in the form of backward warping has seen broad adoption in tasks like depth estimation and optical flow prediction. In contrast, how to perform forwar…

cs.CV201911 cited

Context-Aware Image Matting for Simultaneous Foreground and Alpha Estimation

Qiqi Hou, Feng Liu

Natural image matting is an important problem in computer vision and graphics. It is an ill-posed problem when only an input image is available without any external information. Wh…

cs.CV2019

3D Ken Burns Effect from a Single Image

Simon Niklaus, Long Mai, Jimei Yang +1

The Ken Burns effect allows animating still images with a virtual camera scan and zoom. Adding parallax, which results in the 3D Ken Burns effect, enables significantly more compel…

cs.CV201772 cited

Video Frame Interpolation via Adaptive Separable Convolution

Simon Niklaus, Long Mai, Feng Liu

Standard video frame interpolation methods first estimate optical flow between input frames and then synthesize an intermediate frame guided by motion. Recent approaches merge thes…