title: 360^circ Reconstruction From a Single Image Using Space Carved
    Outpainting
summary: We introduce POP3D, a novel framework that creates a full 360^circ-view 3D
  model from a single image. POP3D resolves two prominent issues that limit the
  single-view reconstruction. Firstly, POP3D offers substantial generalizability
  to arbitrary categories, a trait that previous methods struggle to achieve.
  Secondly, POP3D further improves reconstruction fidelity and naturalness, a
  crucial aspect that concurrent works fall short of. Our approach marries the
  strengths of four primary components: (1) a monocular depth and normal
  predictor that serves to predict crucial geometric cues, (2) a space carving
  method capable of demarcating the potentially unseen portions of the target
  object, (3) a generative model pre-trained on a large-scale image dataset that
  can complete unseen regions of the target, and (4) a neural implicit surface
  reconstruction method tailored in reconstructing objects using RGB images along
  with monocular geometric cues. The combination of these components enables
  POP3D to readily generalize across various in-the-wild images and generate
  state-of-the-art reconstructions, outperforming similar works by a significant
  margin. Project page: http://cg.postech.ac.kr/research/POP3D
paper_authors._id: 650a5b67948ce5dce8d072d8
paper_authors.name: Nuri Ryu
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2023-09-25T10:52:04.136Z
paper_authors._id: 63106aac95c34b954078ef67
paper_authors.avatarUrl: /avatars/0e627c74d301d65f3b364e8229dd78ab.svg
paper_authors.fullname: Nuri Ryu
paper_authors.type: user
paper_authors.user: terryryu
paper_authors._id: 650a5b67948ce5dce8d072d9
paper_authors.name: Minsu Gong
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-09-20T11:55:59.162Z
paper_authors._id: 6412f01b251f9368f690a536
paper_authors.avatarUrl: /avatars/32addb8b2d4cf5babf7ca2284497c847.svg
paper_authors.fullname: Minsu Gong
paper_authors.type: user
paper_authors.user: gongms
paper_authors._id: 650a5b67948ce5dce8d072da
paper_authors.name: Geonung Kim
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-09-20T11:56:06.330Z
paper_authors._id: 63040f5c7373aacccd889430
paper_authors.avatarUrl: /avatars/29b05c69445c48943f535ad381fb9464.svg
paper_authors.fullname: geonung kim
paper_authors.type: user
paper_authors.user: comar
paper_authors._id: 650a5b67948ce5dce8d072db
paper_authors.name: Joo-Haeng Lee
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-09-20T11:56:13.269Z
paper_authors._id: 62d562635c29ac61fec7ae38
paper_authors.avatarUrl: /avatars/816ec718442fa541a21a02b29070e08a.svg
paper_authors.fullname: Joo-Haeng Lee
paper_authors.type: user
paper_authors.user: joohaeng
paper_authors._id: 650a5b67948ce5dce8d072dc
paper_authors.name: Sunghyun Cho
paper_title: 360^circ Reconstruction From a Single Image Using Space Carved
    Outpainting
paper_summary: We introduce POP3D, a novel framework that creates a full 360^circ-view 3D
  model from a single image. POP3D resolves two prominent issues that limit the
  single-view reconstruction. Firstly, POP3D offers substantial generalizability
  to arbitrary categories, a trait that previous methods struggle to achieve.
  Secondly, POP3D further improves reconstruction fidelity and naturalness, a
  crucial aspect that concurrent works fall short of. Our approach marries the
  strengths of four primary components: (1) a monocular depth and normal
  predictor that serves to predict crucial geometric cues, (2) a space carving
  method capable of demarcating the potentially unseen portions of the target
  object, (3) a generative model pre-trained on a large-scale image dataset that
  can complete unseen regions of the target, and (4) a neural implicit surface
  reconstruction method tailored in reconstructing objects using RGB images along
  with monocular geometric cues. The combination of these components enables
  POP3D to readily generalize across various in-the-wild images and generate
  state-of-the-art reconstructions, outperforming similar works by a significant
  margin. Project page: http://cg.postech.ac.kr/research/POP3D
paper_ai_summary: POP3D is a framework that creates a 360-degree 3D model from a single image using a combination of depth prediction, space carving, generative modeling, and neural implicit surfaces.
paper_ai_keywords: monocular depth monocular normal predictor space carving generative model neural implicit surface reconstruction