3 citations · 8 across the 5 of their papers we have counts for
5 papers
The DEVIL is in the Details: A Diagnostic Evaluation Benchmark for Video Inpainting
Ryan Szeto, Jason J. Corso
Quantitative evaluation has increased dramatically among recent video inpainting work, but the video and mask content used to gauge performance has received relatively little atten…
HyperCon: Image-To-Video Model Transfer for Video-To-Video Translation Tasks
Ryan Szeto, Mostafa El-Khamy, Jungwon Lee +1
Video-to-video translation is more difficult than image-to-image translation due to the temporal consistency problem that, if unaddressed, leads to distracting flickering effects.…
A Dataset To Evaluate The Representations Learned By Video Prediction Models
Ryan Szeto, Simon Stent, German Ros +1
We present a parameterized synthetic dataset called Moving Symbols to support the objective study of video prediction networks. Using several instantiations of the dataset in which…
A Temporally-Aware Interpolation Network for Video Frame Inpainting
Ximeng Sun, Ryan Szeto, Jason J. Corso
We propose the first deep learning solution to video frame inpainting, a challenging instance of the general video inpainting problem with applications in video editing, manipulati…
Click Here: Human-Localized Keypoints as Guidance for Viewpoint Estimation
Ryan Szeto, Jason J. Corso
We motivate and address a human-in-the-loop variant of the monocular viewpoint estimation task in which the location and class of one semantic object keypoint is available at test…