arXiv Computer Vision
ReMATF: Recurrent Motion-Adaptive Multi-scale Turbulence Mitigation for Dynamic Scenes
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TriINR: Unsupervised Atmospheric Turbulence Mitigation with Triple Implicit Neural Representations
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arXiv AI
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FMA-Net++: Motion- and Exposure-Aware Joint Video Super-Resolution and Deblurring
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ScanFocus: A Coarse-to-Fine Framework for Spatio-Temporal Video Grounding
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DecoGS: Adaptive Static-Dynamic Decoupling of 3D Gaussians for Free-Viewpoint Video Streaming
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arXiv Computer Vision
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S3VD: Semantic-Guidance Spatio-Temporal Scanning for Video Deraining
S3VD is a new video deraining framework that leverages semantic guidance and spatio‑temporal scanning to improve performance over existing State Space Models such as Mamba. It introduces a Multi‑Scale Semantic Fusion module that uses DINOv2 priors to preserve 2D spatial semantics, and a Spatio‑Temporal Scanning Fusion module that incorporates a Decoupled‑Gating Mamba layer to better model intra‑ and inter‑frame correlations. Experiments on video deraining benchmarks show that S3VD achieves state‑of‑the‑art results, improving PSNR by an average of 0.84 dB over Mamba‑based baselines.
arXiv Machine Learning
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