Search Results for author:
Found 8 papers, 4 papers with code
Scaling 4D Representations
Scaling has not yet been convincingly demonstrated for pure self-supervised learning from video.
Dense Optical Tracking: Connecting the Dots
Code, data, and videos showcasing the capabilities of our approach are available in the project webpage: https://16lemoing. github. io/dot .
WALDO: Future Video Synthesis using Object Layer Decomposition and Parametric Flow Prediction
This paper presents WALDO (WArping Layer-Decomposed Objects), a novel approach to the prediction of future video frames from past ones.
CCVS: Context-aware Controllable Video Synthesis
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.
Ranked #8 on
Video Generation
on BAIR Robot Pushing
Semantic Palette: Guiding Scene Generation with Class Proportions
Despite the recent progress of generative adversarial networks (GANs) at synthesizing photo-realistic images, producing complex urban scenes remains a challenging problem.
Data-Efficient Framework for Real-world Multiple Sound Source 2D Localization
Moreover, learning for different microphone array layouts makes the task more complicated due to the infinite number of possible layouts.
Learning Multiple Sound Source 2D Localization
In this paper, we propose novel deep learning based algorithms for multiple sound source localization.
Ensemble of Discriminators for Domain Adaptation in Multiple Sound Source 2D Localization
This paper introduces an ensemble of discriminators that improves the accuracy of a domain adaptation technique for the localization of multiple sound sources.
