MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian
  Splatting
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. Then the
motion flow can effectively constrain the deformation of 3D Gaussians, thus
simulating the motion of dynamic objects. Additionally, a camera pose
refinement module is proposed to alternately optimize 3D Gaussians and camera
poses, mitigating the impact of inaccurate camera poses. Extensive experiments
in the monocular dynamic scenes validate that MotionGS surpasses
state-of-the-art methods and exhibits significant superiority in both
qualitative and quantitative results. Project page:
https://ruijiezhu94.github.io/MotionGS_page
6708d1a04930ad02cb96781c
Ruijie Zhu
claimed_verified
2024-10-11T07:54:19.427Z
6697ac8427e4e21a3a92da27
https://cdn-avatars.huggingface.co/v1/production/uploads/6697ac8427e4e21a3a92da27/9vn07-1_BBDk9zfDtDpcG.png
Ruijie Zhu
user
RuijieZhu
6708d1a04930ad02cb96781d
Yanzhe Liang
admin_assigned
2024-10-11T11:01:13.469Z
64e817132292cd13a0a69551
https://cdn-avatars.huggingface.co/v1/production/uploads/64e817132292cd13a0a69551/mwJNGHFGL3IdiC45A5WHQ.png
Yanzhe Liang
user
Rosetta-Leong
6708d1a04930ad02cb96781e
Hanzhi Chang
6708d1a04930ad02cb96781f
Jiacheng Deng
admin_assigned
2024-10-11T11:01:40.586Z
666f03e2303f0a5d675a109d
/avatars/5b0dab6a0c1a21d1c729a371aaa0c122.svg
Jiacheng Deng
user
Free1unch
6708d1a04930ad02cb967820
Jiahao Lu
admin_assigned
2024-10-11T11:01:50.523Z
64d3abeb1058ae59738ba8ce
/avatars/4a9de3db835ade2c20f0d2de678e85c4.svg
jiahao lu
user
jiahao97
6708d1a04930ad02cb967821
Wenfei Yang
6708d1a04930ad02cb967822
Tianzhu Zhang
admin_assigned
2024-10-11T11:02:08.108Z
662b8d0083de3e26a6d9f1d1
/avatars/d9566ba1881f86413f5de10a45f24673.svg
Tianzhu Zhang
user
ztz1989
6708d1a04930ad02cb967823
Yongdong Zhang
MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian
  Splatting
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. Then the
motion flow can effectively constrain the deformation of 3D Gaussians, thus
simulating the motion of dynamic objects. Additionally, a camera pose
refinement module is proposed to alternately optimize 3D Gaussians and camera
poses, mitigating the impact of inaccurate camera poses. Extensive experiments
in the monocular dynamic scenes validate that MotionGS surpasses
state-of-the-art methods and exhibits significant superiority in both
qualitative and quantitative results. Project page:
https://ruijiezhu94.github.io/MotionGS_page
MotionGS, a novel deformable 3D Gaussian splatting framework, leverages explicit motion priors and camera pose refinement to improve dynamic scene reconstruction accuracy.
3D Gaussian Splatting MotionGS optical flow decoupling camera flow motion flow camera pose refinement dynamic scene reconstruction