A procedural augmentation pipeline that generates refractive distortions and weather artifacts on African dashcam footage, with restoration baselines and a benchmark for low-resource autonomous perception.
Divergence-Free Shape Interpolation and Correspondence
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abstract
We present a novel method to model and calculate deformation fields between shapes embedded in $\mathbb{R}^D$. Our framework combines naturally interpolating the two input shapes and calculating correspondences at the same time. The key idea is to compute a divergence-free deformation field represented in a coarse-to-fine basis using the Karhunen-Lo\`eve expansion. The advantages are that there is no need to discretize the embedding space and the deformation is volume-preserving. Furthermore, the optimization is done on downsampled versions of the shapes but the morphing can be applied to any resolution without a heavy increase in complexity. We show results for shape correspondence, registration, inter- and extrapolation on the TOSCA and FAUST data sets.
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Simulating Refractive Distortions and Weather-Induced Artifacts for Resource-Constrained Autonomous Perception
A procedural augmentation pipeline that generates refractive distortions and weather artifacts on African dashcam footage, with restoration baselines and a benchmark for low-resource autonomous perception.