TK-Planes: Tiered K-Planes with High Dimensional Feature Vectors for Dynamic UAV-based Scenes

arXiv:2405.02762v1 Announce Type: cross
Abstract: In this paper, we present a new approach to bridge the domain gap between synthetic and real-world data for un- manned aerial vehicle (UAV)-based perception. Our formu- lation is designed for dynamic scenes, consisting of moving objects or human actions, where the goal is to recognize the pose or actions. We propose an extension of K-Planes Neural Radiance Field (NeRF), wherein our algorithm stores a set of tiered feature vectors. The tiered feature vectors are …

abstract aerial arxiv bridge cs.cv cs.lg cs.ro data domain dynamic feature gap human moving objects paper perception planes synthetic type vectors world