most citedCCVS: Context-aware Controllable Video Synthesis

30 citations · 35 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV202130 cited

CCVS: Context-aware Controllable Video Synthesis

Guillaume Le Moing, Jean Ponce, Cordelia Schmid

This presentation introduces a self-supervised learning approach to the synthesis of new video clips from old ones, with several new key elements for improved spatial resolution an…

cs.CV20211 cited

Semantic Palette: Guiding Scene Generation with Class Proportions

Guillaume Le Moing, Tuan-Hung Vu, Himalaya Jain +2

Despite the recent progress of generative adversarial networks (GANs) at synthesizing photo-realistic images, producing complex urban scenes remains a challenging problem. Previous…

eess.AS2020

Learning Multiple Sound Source 2D Localization

Guillaume Le Moing, Phongtharin Vinayavekhin, Tadanobu Inoue +4

In this paper, we propose novel deep learning based algorithms for multiple sound source localization. Specifically, we aim to find the 2D Cartesian coordinates of multiple sound s…

eess.AS20201 cited

Ensemble of Discriminators for Domain Adaptation in Multiple Sound Source 2D Localization

Guillaume Le Moing, Don Joven Agravante, Tadanobu Inoue +4

This paper introduces an ensemble of discriminators that improves the accuracy of a domain adaptation technique for the localization of multiple sound sources. Recently, deep neura…

eess.AS20203 cited

Data-Efficient Framework for Real-world Multiple Sound Source 2D Localization

Guillaume Le Moing, Phongtharin Vinayavekhin, Don Joven Agravante +4

Deep neural networks have recently led to promising results for the task of multiple sound source localization. Yet, they require a lot of training data to cover a variety of acous…