MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian Splatting
–Neural Information Processing Systems
Dynamic scene reconstruction is a long-term challenge in the field of 3D vision. Recently, the emergence of 3D Gaussian Splatting has provided new insights into this problem. Although subsequent efforts rapidly extend static 3D Gaussian to dynamic scenes, they often lack explicit constraints on object motion, leading to optimization difficulties and performance degradation. To address the above issues, we propose a novel deformable 3D Gaussian splatting framework called MotionGS, which explores explicit motion priors to guide the deformation of 3D Gaussians. Specifically, we first introduce an optical flow decoupling module that decouples optical flow into camera flow and motion flow, corresponding to camera movement and object motion respectively.
Neural Information Processing Systems
May-27-2025, 14:03:28 GMT
- Technology:
- Information Technology > Artificial Intelligence > Vision (1.00)