DenZa-Gaussian adapts 3D Gaussian Splatting for ADF-STEM tomography by modeling scattering as a learnable scalar field, adding tilt-angle normalization, and using a Fourier amplitude loss to improve sparse-view 3D reconstructions.
3d u-net: learning dense volumetric segmentation from sparse annotation
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.CV 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
A temporal adapter injects adjacent-slice context into VLM token representations, raising mean Dice from 0.498 to 0.704 on FLARE22 and reducing cross-domain drop from 38% to 24.9%.
VoxSAMNet introduces sparsity-aware deformable attention via a dummy node and foreground modulation with dropout plus text-guided filtering to reach new state-of-the-art mIoU of 18.2% on SemanticKITTI and 20.2% on SSCBench-KITTI-360 for monocular 3D scene completion.
citing papers explorer
-
3D Gaussian Splatting for Annular Dark Field Scanning Transmission Electron Microscopy Tomography Reconstruction
DenZa-Gaussian adapts 3D Gaussian Splatting for ADF-STEM tomography by modeling scattering as a learnable scalar field, adding tilt-angle normalization, and using a Fourier amplitude loss to improve sparse-view 3D reconstructions.
-
T-Gated Adapter: A Lightweight Temporal Adapter for Vision-Language Medical Segmentation
A temporal adapter injects adjacent-slice context into VLM token representations, raising mean Dice from 0.498 to 0.704 on FLARE22 and reducing cross-domain drop from 38% to 24.9%.
-
Sparsity-Aware Voxel Attention and Foreground Modulation for 3D Semantic Scene Completion
VoxSAMNet introduces sparsity-aware deformable attention via a dummy node and foreground modulation with dropout plus text-guided filtering to reach new state-of-the-art mIoU of 18.2% on SemanticKITTI and 20.2% on SSCBench-KITTI-360 for monocular 3D scene completion.