تقرير
HarmonyView: Harmonizing Consistency and Diversity in One-Image-to-3D
| العنوان: | HarmonyView: Harmonizing Consistency and Diversity in One-Image-to-3D |
|---|---|
| المؤلفون: | Woo, Sangmin, Park, Byeongjun, Go, Hyojun, Kim, Jin-Young, Kim, Changick |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence |
| الوصف: | Recent progress in single-image 3D generation highlights the importance of multi-view coherency, leveraging 3D priors from large-scale diffusion models pretrained on Internet-scale images. However, the aspect of novel-view diversity remains underexplored within the research landscape due to the ambiguity in converting a 2D image into 3D content, where numerous potential shapes can emerge. Here, we aim to address this research gap by simultaneously addressing both consistency and diversity. Yet, striking a balance between these two aspects poses a considerable challenge due to their inherent trade-offs. This work introduces HarmonyView, a simple yet effective diffusion sampling technique adept at decomposing two intricate aspects in single-image 3D generation: consistency and diversity. This approach paves the way for a more nuanced exploration of the two critical dimensions within the sampling process. Moreover, we propose a new evaluation metric based on CLIP image and text encoders to comprehensively assess the diversity of the generated views, which closely aligns with human evaluators' judgments. In experiments, HarmonyView achieves a harmonious balance, demonstrating a win-win scenario in both consistency and diversity. Comment: Project page: https://byeongjun-park.github.io/HarmonyView/ |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2312.15980 |
| رقم الأكسشن: | edsarx.2312.15980 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |