SOURCE-LINKED INTELLIGENCE
WS-NeRF: A Mamba-Driven World-State-Aware Adaptive Deblurring Neural Radiance Field
Neural Radiance Fields (NeRF) have attracted extensive attention in recent years due to their strong capability for high-quality 3D reconstruction and novel view synthesis from multi-view images. Existing methods usually rely on high-quality sharp inputs, while real-world image acquisition is highly susceptible to blur degradation, which severely affects the reconstruction quality of NeRF. In this paper, we propose a novel Mamba-driven world-state-aware adaptive deblurring neural radiance field, termed WS-NeRF, to address image degradation and 3D inconsistency. We formulate the alternating opt
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T07:00:35.000Z
First collected: 2026-09-23T14:01:59.594Z. This is not the publication date.