title: WideRange4D: Enabling High-Quality 4D Reconstruction with Wide-Range
    Movements and Scenes
summary: With the rapid development of 3D reconstruction technology, research in 4D
  reconstruction is also advancing, existing 4D reconstruction methods can
  generate high-quality 4D scenes. However, due to the challenges in acquiring
  multi-view video data, the current 4D reconstruction benchmarks mainly display
  actions performed in place, such as dancing, within limited scenarios. In
  practical scenarios, many scenes involve wide-range spatial movements,
  highlighting the limitations of existing 4D reconstruction datasets.
  Additionally, existing 4D reconstruction methods rely on deformation fields to
  estimate the dynamics of 3D objects, but deformation fields struggle with
  wide-range spatial movements, which limits the ability to achieve high-quality
  4D scene reconstruction with wide-range spatial movements. In this paper, we
  focus on 4D scene reconstruction with significant object spatial movements and
  propose a novel 4D reconstruction benchmark, WideRange4D. This benchmark
  includes rich 4D scene data with large spatial variations, allowing for a more
  comprehensive evaluation of the generation capabilities of 4D generation
  methods. Furthermore, we introduce a new 4D reconstruction method, Progress4D,
  which generates stable and high-quality 4D results across various complex 4D
  scene reconstruction tasks. We conduct both quantitative and qualitative
  comparison experiments on WideRange4D, showing that our Progress4D outperforms
  existing state-of-the-art 4D reconstruction methods. Project:
  https://github.com/Gen-Verse/WideRange4D
paper_authors._id: 67d8dd0b924be985c277c8f6
paper_authors.name: Ling Yang
paper_authors.status: admin_assigned
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paper_authors.fullname: Ling Yang
paper_authors.type: user
paper_authors.user: Lingaaaaaaa
paper_authors._id: 67d8dd0b924be985c277c8f7
paper_authors.name: Kaixin Zhu
paper_authors.status: claimed_verified
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paper_authors.fullname: kaixin zhu
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paper_authors.user: czkk566
paper_authors._id: 67d8dd0b924be985c277c8f8
paper_authors.name: Juanxi Tian
paper_authors.status: claimed_verified
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paper_authors.fullname: Juanxi Tian
paper_authors.type: user
paper_authors.user: Juanxi
paper_authors._id: 67d8dd0b924be985c277c8f9
paper_authors.name: Bohan Zeng
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-03-18T08:08:15.654Z
paper_authors._id: 6671214c92412fd4640714eb
paper_authors.avatarUrl: /avatars/48fa84e7bc3bb92ad0192aa26b32de10.svg
paper_authors.fullname: bohan zeng
paper_authors.type: user
paper_authors.user: zbhpku
paper_authors._id: 67d8dd0b924be985c277c8fa
paper_authors.name: Mingbao Lin
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2025-03-18T09:22:58.991Z
paper_authors._id: 64a2a8127adb12be606ec33e
paper_authors.avatarUrl: /avatars/f85dc39a23727a4d50f8a5f5a3865b0d.svg
paper_authors.fullname: Mingbao Lin
paper_authors.type: user
paper_authors.user: mingbao
paper_authors._id: 67d8dd0b924be985c277c8fb
paper_authors.name: Hongjuan Pei
paper_authors._id: 67d8dd0b924be985c277c8fc
paper_authors.name: Wentao Zhang
paper_authors._id: 67d8dd0b924be985c277c8fd
paper_authors.name: Shuicheng Yan
paper_title: WideRange4D: Enabling High-Quality 4D Reconstruction with Wide-Range
    Movements and Scenes
paper_summary: With the rapid development of 3D reconstruction technology, research in 4D
  reconstruction is also advancing, existing 4D reconstruction methods can
  generate high-quality 4D scenes. However, due to the challenges in acquiring
  multi-view video data, the current 4D reconstruction benchmarks mainly display
  actions performed in place, such as dancing, within limited scenarios. In
  practical scenarios, many scenes involve wide-range spatial movements,
  highlighting the limitations of existing 4D reconstruction datasets.
  Additionally, existing 4D reconstruction methods rely on deformation fields to
  estimate the dynamics of 3D objects, but deformation fields struggle with
  wide-range spatial movements, which limits the ability to achieve high-quality
  4D scene reconstruction with wide-range spatial movements. In this paper, we
  focus on 4D scene reconstruction with significant object spatial movements and
  propose a novel 4D reconstruction benchmark, WideRange4D. This benchmark
  includes rich 4D scene data with large spatial variations, allowing for a more
  comprehensive evaluation of the generation capabilities of 4D generation
  methods. Furthermore, we introduce a new 4D reconstruction method, Progress4D,
  which generates stable and high-quality 4D results across various complex 4D
  scene reconstruction tasks. We conduct both quantitative and qualitative
  comparison experiments on WideRange4D, showing that our Progress4D outperforms
  existing state-of-the-art 4D reconstruction methods. Project:
  https://github.com/Gen-Verse/WideRange4D
paper_ai_summary: A novel 4D reconstruction benchmark, WideRange4D, and method, Progress4D, are introduced to address challenges in reconstructing scenes with wide-range object spatial movements.
paper_ai_keywords: 4D reconstruction 4D scene data large spatial variations deformation fields wide-range spatial movements Progress4D WideRange4D 4D generation methods