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.
Learning semantics-aware distance map with semantics layering network for amodal instance segmentation
2 Pith papers cite this work. Polarity classification is still indexing.
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Amodal SAM extends SAM with a Spatial Completion Adapter, Target-Aware Occlusion Synthesis for data, and consistency losses to reach SOTA amodal segmentation with strong generalization to new objects and scenes.
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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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Amodal SAM: A Unified Amodal Segmentation Framework with Generalization
Amodal SAM extends SAM with a Spatial Completion Adapter, Target-Aware Occlusion Synthesis for data, and consistency losses to reach SOTA amodal segmentation with strong generalization to new objects and scenes.