Scene-adaptive nonlinear tone curves (ASE and AP3) with percentile normalisation and offset outperform linear gain for pseudo-GT generation in low-light 3DGS, delivering PSNR gains up to 4.34 dB on LOM and 3.25 dB on RealX3D across 21 scenes.
EnlightenGAN: Deep light enhancement without paired supervision,
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
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cs.CV 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
DelowlightSplat adds a lightweight Lowlight Adapter and cost-volume multi-view inference to feed-forward Gaussian splatting, enabling direct prediction of clean 3D Gaussians from degraded lowlight context views.
MSCGC-KAN adds multi-scale causal graph convolution and Kolmogorov-Arnold feature mapping as a structured task head on a pre-trained CBraMod backbone, reporting balanced accuracy gains of 5.91 and 2.03 points on FACED and SEED-VII datasets over a linear baseline.
citing papers explorer
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Scene-Adaptive Nonlinear Tone Curves for Pseudo Ground-Truth Generation in Low-Light 3D Gaussian Splatting
Scene-adaptive nonlinear tone curves (ASE and AP3) with percentile normalisation and offset outperform linear gain for pseudo-GT generation in low-light 3DGS, delivering PSNR gains up to 4.34 dB on LOM and 3.25 dB on RealX3D across 21 scenes.
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DelowlightSplat: Feed-Forward Gaussian Splatting for Lowlight 3D Scene Reconstruction
DelowlightSplat adds a lightweight Lowlight Adapter and cost-volume multi-view inference to feed-forward Gaussian splatting, enabling direct prediction of clean 3D Gaussians from degraded lowlight context views.
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MSCGC-KAN: Multi-scale Causal Graph Convolution and Kolmogorov-Arnold Feature Mapping for EEG Emotion Recognition
MSCGC-KAN adds multi-scale causal graph convolution and Kolmogorov-Arnold feature mapping as a structured task head on a pre-trained CBraMod backbone, reporting balanced accuracy gains of 5.91 and 2.03 points on FACED and SEED-VII datasets over a linear baseline.