35 citations · 68 across the 6 of their papers we have counts for
8 papers
Temporally smooth online action detection using cycle-consistent future anticipation
Young Hwi Kim, Seonghyeon Nam, Seon Joo Kim
Many video understanding tasks work in the offline setting by assuming that the input video is given from the start to the end. However, many real-world problems require the online…
Cross-Identity Motion Transfer for Arbitrary Objects through Pose-Attentive Video Reassembling
Subin Jeon, Seonghyeon Nam, Seoung Wug Oh +1
We propose an attention-based networks for transferring motions between arbitrary objects. Given a source image(s) and a driving video, our networks animate the subject in the sour…
Learning the Loss Functions in a Discriminative Space for Video Restoration
Younghyun Jo, Jaeyeon Kang, Seoung Wug Oh +3
With more advanced deep network architectures and learning schemes such as GANs, the performance of video restoration algorithms has greatly improved recently. Meanwhile, the loss…
Unsupervised Keypoint Learning for Guiding Class-Conditional Video Prediction
Yunji Kim, Seonghyeon Nam, In Cho +1
We propose a deep video prediction model conditioned on a single image and an action class. To generate future frames, we first detect keypoints of a moving object and predict futu…
End-to-End Time-Lapse Video Synthesis from a Single Outdoor Image
Seonghyeon Nam, Chongyang Ma, Menglei Chai +3
Time-lapse videos usually contain visually appealing content but are often difficult and costly to create. In this paper, we present an end-to-end solution to synthesize a time-lap…
Text-Adaptive Generative Adversarial Networks: Manipulating Images with Natural Language
Seonghyeon Nam, Yunji Kim, Seon Joo Kim
This paper addresses the problem of manipulating images using natural language description. Our task aims to semantically modify visual attributes of an object in an image accordin…