Ground4D resolves temporal conflicts in feedforward 4D Gaussian reconstruction for off-road scenes via voxel-grounded temporal aggregation with intra-voxel softmax and surface normal regularization, outperforming prior methods on ORAD-3D and RELLIS-3D while generalizing zero-shot.
InACM SIGGRAPH 2024 conference papers
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MAGS-SLAM is the first monocular multi-agent Gaussian Splatting SLAM system, aligning independently scaled sub-maps with a Sim(3) pose graph and occupancy-aware Gaussian fusion.
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Ground4D: Spatially-Grounded Feedforward 4D Reconstruction for Unstructured Off-Road Scenes
Ground4D resolves temporal conflicts in feedforward 4D Gaussian reconstruction for off-road scenes via voxel-grounded temporal aggregation with intra-voxel softmax and surface normal regularization, outperforming prior methods on ORAD-3D and RELLIS-3D while generalizing zero-shot.
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MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction
MAGS-SLAM is the first monocular multi-agent Gaussian Splatting SLAM system, aligning independently scaled sub-maps with a Sim(3) pose graph and occupancy-aware Gaussian fusion.