Hierarchical latent structure for multi-modal vehicle trajectory forecasting

D Choi, KW Min - European Conference on Computer Vision, 2022 - Springer
Variational autoencoder (VAE) has widely been utilized for modeling data distributions
because it is theoretically elegant, easy to train, and has nice manifold representations …
被引用次数：14 相关文章

Hierarchical Latent Structure for Multi-modal Vehicle Trajectory Forecasting

D Choi, KW Min - European Conference on Computer Vision, 2022 - dl.acm.org
Variational autoencoder (VAE) has widely been utilized for modeling data distributions
because it is theoretically elegant, easy to train, and has nice manifold representations …
[PDF] ecva.net

[PDF][PDF] Hierarchical Latent Structure for Multi-Modal Vehicle Trajectory Forecasting

D Choi, KW Min - ecva.net
Variational autoencoder (VAE) has widely been utilized for modeling data distributions
because it is theoretically elegant, easy to train, and has nice manifold representations …

Hierarchical Latent Structure for Multi-Modal Vehicle Trajectory Forecasting

D Choi, KW Min - arXiv preprint arXiv:2207.04624, 2022 - arxiv.org
Variational autoencoder (VAE) has widely been utilized for modeling data distributions
because it is theoretically elegant, easy to train, and has nice manifold representations …

Hierarchical Latent Structure for Multi-Modal Vehicle Trajectory Forecasting

D Choi, KW Min - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
Variational autoencoder (VAE) has widely been utilized for modeling data distributions
because it is theoretically elegant, easy to train, and has nice manifold representations …