360^circ Reconstruction From a Single Image Using Space Carved
  Outpainting
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
650a5b67948ce5dce8d072d8
Nuri Ryu
claimed_verified
2023-09-25T10:52:04.136Z
63106aac95c34b954078ef67
/avatars/0e627c74d301d65f3b364e8229dd78ab.svg
Nuri Ryu
user
terryryu
650a5b67948ce5dce8d072d9
Minsu Gong
admin_assigned
2023-09-20T11:55:59.162Z
6412f01b251f9368f690a536
/avatars/32addb8b2d4cf5babf7ca2284497c847.svg
Minsu Gong
user
gongms
650a5b67948ce5dce8d072da
Geonung Kim
admin_assigned
2023-09-20T11:56:06.330Z
63040f5c7373aacccd889430
/avatars/29b05c69445c48943f535ad381fb9464.svg
geonung kim
user
comar
650a5b67948ce5dce8d072db
Joo-Haeng Lee
admin_assigned
2023-09-20T11:56:13.269Z
62d562635c29ac61fec7ae38
/avatars/816ec718442fa541a21a02b29070e08a.svg
Joo-Haeng Lee
user
joohaeng
650a5b67948ce5dce8d072dc
Sunghyun Cho
360^circ Reconstruction From a Single Image Using Space Carved
  Outpainting
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
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.
monocular depth monocular normal predictor space carving generative model neural implicit surface reconstruction