1 code implementation • CVPR 2022 • 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 attention.
no code implementations • 10 Dec 2019 • Ryan Szeto, Mostafa El-Khamy, Jungwon Lee, Jason J. Corso
To combine the benefits of image and video models, we propose an image-to-video model transfer method called Hyperconsistency (HyperCon) that transforms any well-trained image model into a temporally consistent video model without fine-tuning.
1 code implementation • 20 Mar 2018 • 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, manipulation, and forensics.
1 code implementation • 25 Feb 2018 • Ryan Szeto, Simon Stent, German Ros, Jason J. Corso
We present a parameterized synthetic dataset called Moving Symbols to support the objective study of video prediction networks.
no code implementations • ICCV 2017 • 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 time.