论文标题
尖锐的2020:从部分纹理3D扫描挑战结果中恢复的第一形状恢复
SHARP 2020: The 1st Shape Recovery from Partial Textured 3D Scans Challenge Results
论文作者
论文摘要
从部分纹理3D扫描挑战(Sharp 2020)中恢复的形状恢复是挑战和基准测试方法的第一版,用于从原始数据中恢复完整的纹理3D扫描。 Sharp 2020与ECCV 2020结合进行了研讨会。有两个互补的挑战,第一个对3D人类扫描,第二个挑战是通用物体。挑战1进一步分为两条曲目,首先将重点放在大型身体和衣服区域,其次,在细节上。提出了一种新的评估度量,以共同量化形状重建,纹理重建和完整数据的量。此外,提出了两个独特的3D扫描数据集,以提供基准的原始基地真实数据。数据集已发布给科学界。此外,还向科学界发布了随附的软件例程库。它允许处理3D扫描,生成部分数据并执行评估。与基准相比,分析的竞争结果显示了拟议的评估指标的有效性,并强调了任务和数据集的挑战性方面。有关2020年挑战的详细信息,请访问https://cvi2.uni.lu/sharp2020/。
The SHApe Recovery from Partial textured 3D scans challenge, SHARP 2020, is the first edition of a challenge fostering and benchmarking methods for recovering complete textured 3D scans from raw incomplete data. SHARP 2020 is organised as a workshop in conjunction with ECCV 2020. There are two complementary challenges, the first one on 3D human scans, and the second one on generic objects. Challenge 1 is further split into two tracks, focusing, first, on large body and clothing regions, and, second, on fine body details. A novel evaluation metric is proposed to quantify jointly the shape reconstruction, the texture reconstruction and the amount of completed data. Additionally, two unique datasets of 3D scans are proposed, to provide raw ground-truth data for the benchmarks. The datasets are released to the scientific community. Moreover, an accompanying custom library of software routines is also released to the scientific community. It allows for processing 3D scans, generating partial data and performing the evaluation. Results of the competition, analysed in comparison to baselines, show the validity of the proposed evaluation metrics, and highlight the challenging aspects of the task and of the datasets. Details on the SHARP 2020 challenge can be found at https://cvi2.uni.lu/sharp2020/.