Presents the first radar bundle adjustment framework using Gaussian Splatting, integrated with a radar-inertial frontend to reduce average translational and rotational errors by 90% and 80% across indoor scenes.
Nerf: Representing scenes as neural ra- diance fields for view synthesis
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SDTalk proposes a generalizable one-shot 3DGS talking head method that uses structured facial priors for complete reconstruction and dual-branch motion fields for dynamics, outperforming prior identity-specific approaches.
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RadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment
Presents the first radar bundle adjustment framework using Gaussian Splatting, integrated with a radar-inertial frontend to reduce average translational and rotational errors by 90% and 80% across indoor scenes.
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SDTalk: Structured Facial Priors and Dual-Branch Motion Fields for Generalizable Gaussian Talking Head Synthesis
SDTalk proposes a generalizable one-shot 3DGS talking head method that uses structured facial priors for complete reconstruction and dual-branch motion fields for dynamics, outperforming prior identity-specific approaches.