title: WildGaussians: 3D Gaussian Splatting in the Wild
summary: While the field of 3D scene reconstruction is dominated by NeRFs due to their
  photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged,
  offering similar quality with real-time rendering speeds. However, both methods
  primarily excel with well-controlled 3D scenes, while in-the-wild data -
  characterized by occlusions, dynamic objects, and varying illumination -
  remains challenging. NeRFs can adapt to such conditions easily through
  per-image embedding vectors, but 3DGS struggles due to its explicit
  representation and lack of shared parameters. To address this, we introduce
  WildGaussians, a novel approach to handle occlusions and appearance changes
  with 3DGS. By leveraging robust DINO features and integrating an appearance
  modeling module within 3DGS, our method achieves state-of-the-art results. We
  demonstrate that WildGaussians matches the real-time rendering speed of 3DGS
  while surpassing both 3DGS and NeRF baselines in handling in-the-wild data, all
  within a simple architectural framework.
paper_authors._id: 66908e3fd9bea967d8c81afc
paper_authors.name: Jonas Kulhanek
paper_authors.status: claimed_verified
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paper_authors.fullname: Jonáš Kulhánek
paper_authors.type: user
paper_authors.user: jkulhanek
paper_authors._id: 66908e3fd9bea967d8c81afd
paper_authors.name: Songyou Peng
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-07-12T12:13:25.247Z
paper_authors._id: 620cb0722d8bc91e1cf2e6e7
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1644998719617-noauth.jpeg
paper_authors.fullname: Songyou Peng
paper_authors.type: user
paper_authors.user: syp
paper_authors._id: 66908e3fd9bea967d8c81afe
paper_authors.name: Zuzana Kukelova
paper_authors._id: 66908e3fd9bea967d8c81aff
paper_authors.name: Marc Pollefeys
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-02-25T09:42:27.564Z
paper_authors._id: 67b5fa179782a5e2fd2cb26a
paper_authors.avatarUrl: /avatars/62c38f29ec641e001eeddf840bea21a0.svg
paper_authors.fullname: Marc Pollefeys
paper_authors.type: user
paper_authors.user: mapo1
paper_authors._id: 66908e3fd9bea967d8c81b00
paper_authors.name: Torsten Sattler
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2024-07-12T12:13:47.086Z
paper_authors._id: 63105b1a7d9fc84aba584162
paper_authors.avatarUrl: /avatars/d67c8ad72fec8595c2dff7de5dc21964.svg
paper_authors.fullname: Torsten Sattler
paper_authors.type: user
paper_authors.user: tsattler
paper_title: WildGaussians: 3D Gaussian Splatting in the Wild
paper_summary: While the field of 3D scene reconstruction is dominated by NeRFs due to their
  photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged,
  offering similar quality with real-time rendering speeds. However, both methods
  primarily excel with well-controlled 3D scenes, while in-the-wild data -
  characterized by occlusions, dynamic objects, and varying illumination -
  remains challenging. NeRFs can adapt to such conditions easily through
  per-image embedding vectors, but 3DGS struggles due to its explicit
  representation and lack of shared parameters. To address this, we introduce
  WildGaussians, a novel approach to handle occlusions and appearance changes
  with 3DGS. By leveraging robust DINO features and integrating an appearance
  modeling module within 3DGS, our method achieves state-of-the-art results. We
  demonstrate that WildGaussians matches the real-time rendering speed of 3DGS
  while surpassing both 3DGS and NeRF baselines in handling in-the-wild data, all
  within a simple architectural framework.
paper_ai_keywords: NeRFs 3D Gaussian Splatting 3DGS per-image embedding vectors robust DINO features appearance modeling module WildGaussians