Gradient-Applied Weighted Loss for Details of 3D Shape in Single-View Reconstruction Article Swipe
Jiho Lee
,
Taehyeon Kim
,
Gihwan Lee
,
Yoonsik Choe
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202211.0129.v1
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202211.0129.v1
There has been considerable research on reconstructing 3D shapes from single-view images; however, preserving the detailed information of the input image remains difficult. In this paper, we propose the application of a gradient map to train a network, aimed at improving the visual quality of fine-grained details such as the thin and tiny components of generated shapes. Each gradient map was created from the original voxel data, and each value represented the amount of information per volume. Here, the gradient map was defined by several methods that mathematically quantify and represent the detailed structure of an object. By applying this map to the loss function in training, we could induce the network to intensively train partial details, such as thin and narrow parts. We demonstrated that the detailed information was well-recovered when a weight that is proportional to the gradient value was applied to the loss. Furthermore, it is expected that our method will contribute to the development of 3D technologies related to the construction of virtual space for simulation and new customer experience.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.20944/preprints202211.0129.v1
- https://www.preprints.org/manuscript/202211.0129/v1/download
- OA Status
- green
- Cited By
- 1
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4308588611
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4308588611Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.20944/preprints202211.0129.v1Digital Object Identifier
- Title
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Gradient-Applied Weighted Loss for Details of 3D Shape in Single-View ReconstructionWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-11-08Full publication date if available
- Authors
-
Jiho Lee, Taehyeon Kim, Gihwan Lee, Yoonsik ChoeList of authors in order
- Landing page
-
https://doi.org/10.20944/preprints202211.0129.v1Publisher landing page
- PDF URL
-
https://www.preprints.org/manuscript/202211.0129/v1/downloadDirect link to full text PDF
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-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.preprints.org/manuscript/202211.0129/v1/downloadDirect OA link when available
- Concepts
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Computer science, Voxel, Artificial intelligence, Function (biology), Object (grammar), Computer vision, Image (mathematics), Volume (thermodynamics), Evolutionary biology, Physics, Quantum mechanics, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2022: 1Per-year citation counts (last 5 years)
- References (count)
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31Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.narrow | 121 |
| abstract_inverted_index.paper, | 25 |
| abstract_inverted_index.parts. | 122 |
| abstract_inverted_index.shapes | 8 |
| abstract_inverted_index.visual | 42 |
| abstract_inverted_index.weight | 133 |
| abstract_inverted_index.applied | 142 |
| abstract_inverted_index.created | 61 |
| abstract_inverted_index.defined | 82 |
| abstract_inverted_index.details | 46 |
| abstract_inverted_index.images; | 11 |
| abstract_inverted_index.methods | 85 |
| abstract_inverted_index.network | 111 |
| abstract_inverted_index.object. | 96 |
| abstract_inverted_index.partial | 115 |
| abstract_inverted_index.propose | 27 |
| abstract_inverted_index.quality | 43 |
| abstract_inverted_index.related | 161 |
| abstract_inverted_index.remains | 21 |
| abstract_inverted_index.several | 84 |
| abstract_inverted_index.shapes. | 56 |
| abstract_inverted_index.virtual | 166 |
| abstract_inverted_index.volume. | 76 |
| abstract_inverted_index.applying | 98 |
| abstract_inverted_index.customer | 172 |
| abstract_inverted_index.detailed | 15, 92, 127 |
| abstract_inverted_index.details, | 116 |
| abstract_inverted_index.expected | 149 |
| abstract_inverted_index.function | 104 |
| abstract_inverted_index.gradient | 32, 58, 79, 139 |
| abstract_inverted_index.however, | 12 |
| abstract_inverted_index.network, | 37 |
| abstract_inverted_index.original | 64 |
| abstract_inverted_index.quantify | 88 |
| abstract_inverted_index.research | 4 |
| abstract_inverted_index.generated | 55 |
| abstract_inverted_index.improving | 40 |
| abstract_inverted_index.represent | 90 |
| abstract_inverted_index.structure | 93 |
| abstract_inverted_index.training, | 106 |
| abstract_inverted_index.components | 53 |
| abstract_inverted_index.contribute | 154 |
| abstract_inverted_index.difficult. | 22 |
| abstract_inverted_index.preserving | 13 |
| abstract_inverted_index.simulation | 169 |
| abstract_inverted_index.application | 29 |
| abstract_inverted_index.development | 157 |
| abstract_inverted_index.experience. | 173 |
| abstract_inverted_index.information | 16, 74, 128 |
| abstract_inverted_index.intensively | 113 |
| abstract_inverted_index.represented | 70 |
| abstract_inverted_index.single-view | 10 |
| abstract_inverted_index.Furthermore, | 146 |
| abstract_inverted_index.considerable | 3 |
| abstract_inverted_index.construction | 164 |
| abstract_inverted_index.demonstrated | 124 |
| abstract_inverted_index.fine-grained | 45 |
| abstract_inverted_index.proportional | 136 |
| abstract_inverted_index.technologies | 160 |
| abstract_inverted_index.mathematically | 87 |
| abstract_inverted_index.reconstructing | 6 |
| abstract_inverted_index.well-recovered | 130 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.5 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.64450946 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |