title: 4K4D: Real-Time 4D View Synthesis at 4K Resolution
summary: This paper targets high-fidelity and real-time view synthesis of dynamic 3D
  scenes at 4K resolution. Recently, some methods on dynamic view synthesis have
  shown impressive rendering quality. However, their speed is still limited when
  rendering high-resolution images. To overcome this problem, we propose 4K4D, a
  4D point cloud representation that supports hardware rasterization and enables
  unprecedented rendering speed. Our representation is built on a 4D feature grid
  so that the points are naturally regularized and can be robustly optimized. In
  addition, we design a novel hybrid appearance model that significantly boosts
  the rendering quality while preserving efficiency. Moreover, we develop a
  differentiable depth peeling algorithm to effectively learn the proposed model
  from RGB videos. Experiments show that our representation can be rendered at
  over 400 FPS on the DNA-Rendering dataset at 1080p resolution and 80 FPS on the
  ENeRF-Outdoor dataset at 4K resolution using an RTX 4090 GPU, which is 30x
  faster than previous methods and achieves the state-of-the-art rendering
  quality. We will release the code for reproducibility.
paper_authors._id: 652f53617636538890b22742
paper_authors.name: Zhen Xu
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-10-18T08:33:36.488Z
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paper_authors.avatarUrl: /avatars/189666a6b34df4e978d1396108f7cf4a.svg
paper_authors.fullname: Zhen Xu
paper_authors.type: user
paper_authors.user: dendenxu
paper_authors._id: 652f53617636538890b22743
paper_authors.name: Sida Peng
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-10-18T08:34:04.355Z
paper_authors._id: 62986ca2b58e71e2ac9b8f01
paper_authors.avatarUrl: /avatars/83944db5f3dbb6f47c47c46fb2cb2849.svg
paper_authors.fullname: Sida Peng
paper_authors.type: user
paper_authors.user: pengsida
paper_authors._id: 652f53617636538890b22744
paper_authors.name: Haotong Lin
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-10-18T08:06:47.674Z
paper_authors._id: 6489a01b8de3f9d810b0154f
paper_authors.avatarUrl: /avatars/f7a0fc6816535945e11bac1212dd7b57.svg
paper_authors.fullname: Haotong Lin
paper_authors.type: user
paper_authors.user: haotongl
paper_authors._id: 652f53617636538890b22745
paper_authors.name: Guangzhao He
paper_authors._id: 652f53617636538890b22746
paper_authors.name: Jiaming Sun
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-10-18T08:17:39.394Z
paper_authors._id: 63141d8df839c69a68e73201
paper_authors.avatarUrl: /avatars/b25fca555d22987241fd40bb56b8247a.svg
paper_authors.fullname: Jiaming  Sun
paper_authors.type: user
paper_authors.user: jiamingsun
paper_authors._id: 652f53617636538890b22747
paper_authors.name: Yujun Shen
paper_authors._id: 652f53617636538890b22748
paper_authors.name: Hujun Bao
paper_authors._id: 652f53617636538890b22749
paper_authors.name: Xiaowei Zhou
paper_title: 4K4D: Real-Time 4D View Synthesis at 4K Resolution
paper_summary: This paper targets high-fidelity and real-time view synthesis of dynamic 3D
  scenes at 4K resolution. Recently, some methods on dynamic view synthesis have
  shown impressive rendering quality. However, their speed is still limited when
  rendering high-resolution images. To overcome this problem, we propose 4K4D, a
  4D point cloud representation that supports hardware rasterization and enables
  unprecedented rendering speed. Our representation is built on a 4D feature grid
  so that the points are naturally regularized and can be robustly optimized. In
  addition, we design a novel hybrid appearance model that significantly boosts
  the rendering quality while preserving efficiency. Moreover, we develop a
  differentiable depth peeling algorithm to effectively learn the proposed model
  from RGB videos. Experiments show that our representation can be rendered at
  over 400 FPS on the DNA-Rendering dataset at 1080p resolution and 80 FPS on the
  ENeRF-Outdoor dataset at 4K resolution using an RTX 4090 GPU, which is 30x
  faster than previous methods and achieves the state-of-the-art rendering
  quality. We will release the code for reproducibility.
paper_ai_keywords: 4K4D 4D point cloud representation hardware rasterization 4D feature grid rendering quality rendering speed hybrid appearance model differentiable depth peeling algorithm DNA-Rendering dataset ENeRF-Outdoor dataset RTX 4090 GPU