title: MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian
    Splatting
summary: 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
paper_authors._id: 6708d1a04930ad02cb96781c
paper_authors.name: Ruijie Zhu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-10-11T07:54:19.427Z
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paper_authors.fullname: Ruijie Zhu
paper_authors.type: user
paper_authors.user: RuijieZhu
paper_authors._id: 6708d1a04930ad02cb96781d
paper_authors.name: Yanzhe Liang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-10-11T11:01:13.469Z
paper_authors._id: 64e817132292cd13a0a69551
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paper_authors.fullname: Yanzhe Liang
paper_authors.type: user
paper_authors.user: Rosetta-Leong
paper_authors._id: 6708d1a04930ad02cb96781e
paper_authors.name: Hanzhi Chang
paper_authors._id: 6708d1a04930ad02cb96781f
paper_authors.name: Jiacheng Deng
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-10-11T11:01:40.586Z
paper_authors._id: 666f03e2303f0a5d675a109d
paper_authors.avatarUrl: /avatars/5b0dab6a0c1a21d1c729a371aaa0c122.svg
paper_authors.fullname: Jiacheng Deng
paper_authors.type: user
paper_authors.user: Free1unch
paper_authors._id: 6708d1a04930ad02cb967820
paper_authors.name: Jiahao Lu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-10-11T11:01:50.523Z
paper_authors._id: 64d3abeb1058ae59738ba8ce
paper_authors.avatarUrl: /avatars/4a9de3db835ade2c20f0d2de678e85c4.svg
paper_authors.fullname: jiahao lu
paper_authors.type: user
paper_authors.user: jiahao97
paper_authors._id: 6708d1a04930ad02cb967821
paper_authors.name: Wenfei Yang
paper_authors._id: 6708d1a04930ad02cb967822
paper_authors.name: Tianzhu Zhang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-10-11T11:02:08.108Z
paper_authors._id: 662b8d0083de3e26a6d9f1d1
paper_authors.avatarUrl: /avatars/d9566ba1881f86413f5de10a45f24673.svg
paper_authors.fullname: Tianzhu Zhang
paper_authors.type: user
paper_authors.user: ztz1989
paper_authors._id: 6708d1a04930ad02cb967823
paper_authors.name: Yongdong Zhang
paper_title: MotionGS: Exploring Explicit Motion Guidance for Deformable 3D Gaussian
    Splatting
paper_summary: 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
paper_ai_summary: MotionGS, a novel deformable 3D Gaussian splatting framework, leverages explicit motion priors and camera pose refinement to improve dynamic scene reconstruction accuracy.
paper_ai_keywords: 3D Gaussian Splatting MotionGS optical flow decoupling camera flow motion flow camera pose refinement dynamic scene reconstruction