title: Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass
summary: Multi-view 3D reconstruction remains a core challenge in computer vision,
  particularly in applications requiring accurate and scalable representations
  across diverse perspectives. Current leading methods such as DUSt3R employ a
  fundamentally pairwise approach, processing images in pairs and necessitating
  costly global alignment procedures to reconstruct from multiple views. In this
  work, we propose Fast 3D Reconstruction (Fast3R), a novel multi-view
  generalization to DUSt3R that achieves efficient and scalable 3D reconstruction
  by processing many views in parallel. Fast3R's Transformer-based architecture
  forwards N images in a single forward pass, bypassing the need for iterative
  alignment. Through extensive experiments on camera pose estimation and 3D
  reconstruction, Fast3R demonstrates state-of-the-art performance, with
  significant improvements in inference speed and reduced error accumulation.
  These results establish Fast3R as a robust alternative for multi-view
  applications, offering enhanced scalability without compromising reconstruction
  accuracy.
paper_authors._id: 6792f5f6dc641d1a72b00736
paper_authors.name: Jianing Yang
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2025-01-24T09:08:08.128Z
paper_authors._id: 646afdd535c7a57f936d3ff5
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/LsDQPftQrnp_Gvanzim4J.jpeg
paper_authors.fullname: Jed Yang
paper_authors.type: user
paper_authors.user: jedyang97
paper_authors._id: 6792f5f6dc641d1a72b00737
paper_authors.name: Alexander Sax
paper_authors._id: 6792f5f6dc641d1a72b00738
paper_authors.name: Kevin J. Liang
paper_authors._id: 6792f5f6dc641d1a72b00739
paper_authors.name: Mikael Henaff
paper_authors._id: 6792f5f6dc641d1a72b0073a
paper_authors.name: Hao Tang
paper_authors._id: 6792f5f6dc641d1a72b0073b
paper_authors.name: Ang Cao
paper_authors._id: 6792f5f6dc641d1a72b0073c
paper_authors.name: Joyce Chai
paper_authors._id: 6792f5f6dc641d1a72b0073d
paper_authors.name: Franziska Meier
paper_authors._id: 6792f5f6dc641d1a72b0073e
paper_authors.name: Matt Feiszli
paper_title: Fast3R: Towards 3D Reconstruction of 1000+ Images in One Forward Pass
paper_summary: Multi-view 3D reconstruction remains a core challenge in computer vision,
  particularly in applications requiring accurate and scalable representations
  across diverse perspectives. Current leading methods such as DUSt3R employ a
  fundamentally pairwise approach, processing images in pairs and necessitating
  costly global alignment procedures to reconstruct from multiple views. In this
  work, we propose Fast 3D Reconstruction (Fast3R), a novel multi-view
  generalization to DUSt3R that achieves efficient and scalable 3D reconstruction
  by processing many views in parallel. Fast3R's Transformer-based architecture
  forwards N images in a single forward pass, bypassing the need for iterative
  alignment. Through extensive experiments on camera pose estimation and 3D
  reconstruction, Fast3R demonstrates state-of-the-art performance, with
  significant improvements in inference speed and reduced error accumulation.
  These results establish Fast3R as a robust alternative for multi-view
  applications, offering enhanced scalability without compromising reconstruction
  accuracy.
paper_ai_summary: Fast3R, a Transformer-based extension of DUSt3R, achieves efficient and scalable multi-view 3D reconstruction by processing multiple images in parallel, improving inference speed and accuracy.
paper_ai_keywords: multi-view 3D reconstruction DUSt3R Transformer-based architecture camera pose estimation