Feb. 28, 2024, 5:44 a.m. | Faris Janjo\v{s}, Marcel Hallgarten, Anthony Knittel, Maxim Dolgov, Andreas Zell, J. Marius Z\"ollner

cs.LG updates on arXiv.org arxiv.org

arXiv:2310.19944v2 Announce Type: replace-cross
Abstract: The CVAE is one of the most widely-used models in trajectory prediction for AD. It captures the interplay between a driving context and its ground-truth future into a probabilistic latent space and uses it to produce predictions. In this paper, we challenge key components of the CVAE. We leverage recent advances in the space of the VAE, the foundation of the CVAE, which show that a simple change in the sampling procedure can greatly benefit …

arxiv autoencoders cs.ai cs.cv cs.lg cs.ro prediction trajectory type

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