The paper presents a multimodal framework, dataset, and reconstruction pipeline to create immersive volumetric videos supporting large 6-DoF audiovisual interaction from real multi-view captures.
Spacetime gaussian feature splatting for real-time dynamic view synthesis
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.CV 3years
2026 3representative citing papers
Two MoE integration strategies (joint canonical MoDE vs. independent-then-route MoE-GS) improve dynamic Gaussian Splatting by composing complementary deformation priors.
SemDynReg constructs per-object ID maps from SAM and image features to regularize position, scale, and rotation of top-k Gaussians per object in dynamic 3DGS.
citing papers explorer
-
Realizing Immersive Volumetric Video: A Multimodal Framework for 6-DoF VR Engagement
The paper presents a multimodal framework, dataset, and reconstruction pipeline to create immersive volumetric videos supporting large 6-DoF audiovisual interaction from real multi-view captures.
-
On the Design of Mixture-of-Experts for Dynamic Gaussian Splatting
Two MoE integration strategies (joint canonical MoDE vs. independent-then-route MoE-GS) improve dynamic Gaussian Splatting by composing complementary deformation priors.
-
SemDynReg: Semantics-Guided Deformation Regularization for Dynamic 3D Gaussian Splatting
SemDynReg constructs per-object ID maps from SAM and image features to regularize position, scale, and rotation of top-k Gaussians per object in dynamic 3DGS.