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Nick Michiels

4 accepted papers

2026

DASP: Self-Supervised Nighttime Monocular Depth Estimation With Domain Adaptation of Spatiotemporal Priors

RA-L 2026

Self-supervised monocular depth estimation has achieved notable success under daytime conditions. However, its performance deteriorates markedly at night due to low visibility and varying illumination, e.g., insufficient light causes textureless areas, and moving objects bring blurry regions. To thi

Cited by 0SourceScholar
2026

DASP: Self-Supervised Nighttime Monocular Depth Estimation with Domain Adaptation of Spatiotemporal Priors

ICRA 2026poster

Self-supervised monocular depth estimation has achieved notable success under daytime conditions. However, its performance deteriorates markedly at night due to low visibility and varying illumination, e.g., insufficient light causes textureless areas, and moving objects bring blurry regions. To thi…

2026

NVGS: Neural Visibility for Occlusion Culling in 3D Gaussian Splatting

CVPR 2026

3D Gaussian Splatting can exploit frustum culling and level-of-detail strategies to accelerate rendering of scenes containing a large number of primitives. However, the semi-transparent nature of Gaussians prevents the application of another highly effective technique: occlusion culling. We address

Cited by 0SourcecodeScholar
2024

DistillGrasp: Integrating Features Correlation With Knowledge Distillation for Depth Completion of Transparent Objects

RA-L 2024

Due to the visual properties of reflection and refraction, RGB-D cameras cannot accurately capture the depth of transparent objects, leading to incomplete depth maps. To fill in the missing points, recent studies tend to explore new visual features and design complex networks to reconstruct the dept

Cited by 5SourceScholar