Search Results for author: Guillaume Le Moing

Found 7 papers, 4 papers with code

Dense Optical Tracking: Connecting the Dots

1 code implementation1 Dec 2023 Guillaume Le Moing, Jean Ponce, Cordelia Schmid

Code, data, and videos showcasing the capabilities of our approach are available in the project webpage: https://16lemoing. github. io/dot .

Optical Flow Estimation Point Tracking

WALDO: Future Video Synthesis using Object Layer Decomposition and Parametric Flow Prediction

1 code implementation ICCV 2023 Guillaume Le Moing, Jean Ponce, Cordelia Schmid

This paper presents WALDO (WArping Layer-Decomposed Objects), a novel approach to the prediction of future video frames from past ones.

SSIM

CCVS: Context-aware Controllable Video Synthesis

1 code implementation NeurIPS 2021 Guillaume Le Moing, Jean Ponce, Cordelia Schmid

The prediction model is doubly autoregressive, in the latent space of an autoencoder for forecasting, and in image space for updating contextual information, which is also used to enforce spatio-temporal consistency through a learnable optical flow module.

Optical Flow Estimation Self-Supervised Learning +2

Semantic Palette: Guiding Scene Generation with Class Proportions

1 code implementation CVPR 2021 Guillaume Le Moing, Tuan-Hung Vu, Himalaya Jain, Patrick Pérez, Matthieu Cord

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

Data Augmentation Image Generation +1

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

no code implementations10 Dec 2020 Guillaume Le Moing, Phongtharin Vinayavekhin, Don Joven Agravante, Tadanobu Inoue, Jayakorn Vongkulbhisal, Asim Munawar, Ryuki Tachibana

Moreover, learning for different microphone array layouts makes the task more complicated due to the infinite number of possible layouts.

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

no code implementations10 Dec 2020 Guillaume Le Moing, Don Joven Agravante, Tadanobu Inoue, Jayakorn Vongkulbhisal, Asim Munawar, Ryuki Tachibana, Phongtharin Vinayavekhin

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

Domain Adaptation

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