SegForestNet introduces refinements to predict efficient polygon representations using BSP trees, improving spatial partitioning in aerial images. The model's novel loss function enhances region map accuracy and class-specific shape predictions. Training process optimizations enable end-to-end training without an autoencoder phase.
SegForestNet's contributions include improved gradient computations, refined loss functions, and the ability to predict multiple trees per block for precise shape predictions. The model outperforms other state-of-the-art models under optimal training conditions despite non-optimal architecture claims.
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by Dani... às arxiv.org 02-29-2024
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