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.
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.
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.
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 • 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.