activity
20182021
most citedMode Seeking Generative Adversarial Networks for Diverse Image Synthesis

36 citations · 97 across the 11 of their papers we have counts for

collaborators

16 papers

cs.CV2021

Learning to Stylize Novel Views

Hsin-Ping Huang, Hung-Yu Tseng, Saurabh Saini +2

We tackle a 3D scene stylization problem - generating stylized images of a scene from arbitrary novel views given a set of images of the same scene and a reference image of the des…

cs.LG202111 cited

Regularizing Generative Adversarial Networks under Limited Data

Hung-Yu Tseng, Lu Jiang, Ce Liu +2

Recent years have witnessed the rapid progress of generative adversarial networks (GANs). However, the success of the GAN models hinges on a large amount of training data. This wor…

cs.CV20214 cited

Unsupervised Sound Localization via Iterative Contrastive Learning

Yan-Bo Lin, Hung-Yu Tseng, Hsin-Ying Lee +2

Sound localization aims to find the source of the audio signal in the visual scene. However, it is labor-intensive to annotate the correlations between the signals sampled from the…

cs.CV20206 cited

Unsupervised Discovery of Disentangled Manifolds in GANs

Yu-Ding Lu, Hsin-Ying Lee, Hung-Yu Tseng +1

As recent generative models can generate photo-realistic images, people seek to understand the mechanism behind the generation process. Interpretable generation process is benefici…

cs.CV20201 cited

Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors

Qi Mao, Hung-Yu Tseng, Hsin-Ying Lee +3

Recent image-to-image (I2I) translation algorithms focus on learning the mapping from a source to a target domain. However, the continuous translation problem that synthesizes inte…

cs.CV2020

Semantic View Synthesis

Hsin-Ping Huang, Hung-Yu Tseng, Hsin-Ying Lee +1

We tackle a new problem of semantic view synthesis -- generating free-viewpoint rendering of a synthesized scene using a semantic label map as input. We build upon recent advances…