title: 3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes
summary: Recent advances in radiance field reconstruction, such as 3D Gaussian
  Splatting (3DGS), have achieved high-quality novel view synthesis and fast
  rendering by representing scenes with compositions of Gaussian primitives.
  However, 3D Gaussians present several limitations for scene reconstruction.
  Accurately capturing hard edges is challenging without significantly increasing
  the number of Gaussians, creating a large memory footprint. Moreover, they
  struggle to represent flat surfaces, as they are diffused in space. Without
  hand-crafted regularizers, they tend to disperse irregularly around the actual
  surface. To circumvent these issues, we introduce a novel method, named 3D
  Convex Splatting (3DCS), which leverages 3D smooth convexes as primitives for
  modeling geometrically-meaningful radiance fields from multi-view images.
  Smooth convex shapes offer greater flexibility than Gaussians, allowing for a
  better representation of 3D scenes with hard edges and dense volumes using
  fewer primitives. Powered by our efficient CUDA-based rasterizer, 3DCS achieves
  superior performance over 3DGS on benchmarks such as Mip-NeRF360, Tanks and
  Temples, and Deep Blending. Specifically, our method attains an improvement of
  up to 0.81 in PSNR and 0.026 in LPIPS compared to 3DGS while maintaining high
  rendering speeds and reducing the number of required primitives. Our results
  highlight the potential of 3D Convex Splatting to become the new standard for
  high-quality scene reconstruction and novel view synthesis. Project page:
  convexsplatting.github.io.
paper_authors._id: 67486212d54ac635d1e18fef
paper_authors.name: Jan Held
paper_authors._id: 67486212d54ac635d1e18ff0
paper_authors.name: Renaud Vandeghen
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-11-28T21:15:28.839Z
paper_authors._id: 66efc5e1801ea45d7ab2a77b
paper_authors.avatarUrl: /avatars/a37cb36ea7a57315683b45051e9ca5fa.svg
paper_authors.fullname: Renaud Vandeghen
paper_authors.type: user
paper_authors.user: rvandeghen
paper_authors._id: 67486212d54ac635d1e18ff1
paper_authors.name: Abdullah Hamdi
paper_authors._id: 67486212d54ac635d1e18ff2
paper_authors.name: Adrien Deliege
paper_authors._id: 67486212d54ac635d1e18ff3
paper_authors.name: Anthony Cioppa
paper_authors._id: 67486212d54ac635d1e18ff4
paper_authors.name: Silvio Giancola
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-12-02T08:50:48.884Z
paper_authors._id: 666973a3a123f2f8a2aec2b7
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/666973a3a123f2f8a2aec2b7/RRDAa_f1qY58f2iYwsbHi.jpeg
paper_authors.fullname: Silvio Giancola
paper_authors.type: user
paper_authors.user: SilvioGiancola
paper_authors._id: 67486212d54ac635d1e18ff5
paper_authors.name: Andrea Vedaldi
paper_authors._id: 67486212d54ac635d1e18ff6
paper_authors.name: Bernard Ghanem
paper_authors._id: 67486212d54ac635d1e18ff7
paper_authors.name: Marc Van Droogenbroeck
paper_title: 3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes
paper_summary: Recent advances in radiance field reconstruction, such as 3D Gaussian
  Splatting (3DGS), have achieved high-quality novel view synthesis and fast
  rendering by representing scenes with compositions of Gaussian primitives.
  However, 3D Gaussians present several limitations for scene reconstruction.
  Accurately capturing hard edges is challenging without significantly increasing
  the number of Gaussians, creating a large memory footprint. Moreover, they
  struggle to represent flat surfaces, as they are diffused in space. Without
  hand-crafted regularizers, they tend to disperse irregularly around the actual
  surface. To circumvent these issues, we introduce a novel method, named 3D
  Convex Splatting (3DCS), which leverages 3D smooth convexes as primitives for
  modeling geometrically-meaningful radiance fields from multi-view images.
  Smooth convex shapes offer greater flexibility than Gaussians, allowing for a
  better representation of 3D scenes with hard edges and dense volumes using
  fewer primitives. Powered by our efficient CUDA-based rasterizer, 3DCS achieves
  superior performance over 3DGS on benchmarks such as Mip-NeRF360, Tanks and
  Temples, and Deep Blending. Specifically, our method attains an improvement of
  up to 0.81 in PSNR and 0.026 in LPIPS compared to 3DGS while maintaining high
  rendering speeds and reducing the number of required primitives. Our results
  highlight the potential of 3D Convex Splatting to become the new standard for
  high-quality scene reconstruction and novel view synthesis. Project page:
  convexsplatting.github.io.
paper_ai_summary: 3D Convex Splatting achieves superior scene reconstruction and novel view synthesis by using smooth convex shapes, offering improved performance and efficiency compared to 3D Gaussian Splatting.
paper_ai_keywords: 3D Gaussian Splatting (3DGS) 3D Convex Splatting (3DCS) Gaussian primitives radiance fields smooth convexes novel view synthesis CUDA-based rasterizer Mip-NeRF360 Tanks and Temples Deep Blending PSNR LPIPS