We introduce a new hybrid implicit-explicit network architecture and training strategy that adaptively allocates resources during training and inference.

An adaptive coordinate network learns an adaptive decomposition of the signal domain, allowing the network to fit signals faster and more accurately.

Jul 19, 2021 · We introduce a new hybrid implicit-explicit network architecture and training strategy that adaptively allocates resources during training and inference.

Figure 1. Adaptive coordinate networks for neural scene representation (acorn), can fit signals such as three-dimensional occupancy fields with high accuracy.

1. Adaptive coordinate networks for neural scene representation ( ), can fit signals such as three-dimensional occupancy fields with high accuracy.

Sep 6, 2024 · Moreover, our approach is able to represent 3D shapes significantly faster and better than previous techniques; it reduces training times from ...

Here, we introduce a new hybrid implicit-explicit network architecture and training strategy that adaptively allocates resources during training and inference ...

Here, we introduce a new hybrid implicit-explicit network architecture and training strategy that adaptively allocates resources during training and inference ...

ACORN: Adaptive Coordinate Networks for Neural Scene Representation. arXiv.2105.02788, pp. . DOI: https://doi.org/10.48550/arXiv.2105.02788. Martel, Julien ...

DescriptionWe introduce adaptive coordinate networks: a hybrid implicit-explicit neural representation using an online multiscale decomposition to represent ...