Learning from synthetic photorealistic raindrop for single image raindrop removal
Read the original on arXiv Computer Vision →The Flow has not summarised this story yet — read it at arXiv Computer Vision.
The Flow has not summarised this story yet — read it at arXiv Computer Vision.
The paper introduces LLPR, a framework that integrates location-aware learning and physics-based reconstruction to remove raindrops from single images. It replaces costly preprocessing masks with a learnable branch that can be discarded during inference, and reconstructs the background by first estimating a transparency matrix and raindrop layer using a physical model. The authors also present a new real-world dataset and show that LLPR outperforms existing state‑of‑the‑art methods.
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