AI Creates 3D Model of Lost Temple Relief From 134-Year-Old Photo

by time news

Scientists have achieved a remarkable feat by resurrecting a hidden piece of history. Using a simple photograph from the 1800s and cutting-edge AI technology, researchers ‍from Ritsumeikan University in Japan have generated a precise ⁤3D model ⁣of a buried relief sculpture found ⁤within⁢ the ancient Borobudur Temple in Indonesia, a UNESCO World Heritage Site and the world’s largest Buddhist temple complex.

This buried treasure, a relief depicting intricate carvings of‍ figures, was temporarily revealed during restoration work over a century ago. A ⁢black-and-white photograph captured this fleeting moment before the ​relief was carefully reburied. Now, thanks to ​a novel neural⁢ network‍ developed by the research team, this forgotten artwork is brought back to life⁢ in digital form.

Professor Satoshi Tanaka‍ from Ritsumeikan‌ University explains, ​”Our previous method, while ⁣achieving 95% reconstruction accuracy, struggled to‌ capture fine⁢ details like intricate⁤ facial ⁤features and delicate ornamentation due to the inherent limitations of depth compression in​ 2D relief images. Our new approach ⁢directly addresses this challenge ⁣by enhancing depth estimation, particularly along⁣ subtle edges, through a revolutionary edge-detection method.”

The team’s breakthrough lies in a​ multi-modal neural network⁤ that performs three interconnected ⁤tasks:⁣ semantic‌ segmentation, depth estimation,⁢ and⁤ soft-edge detection. This unique combination significantly improves the accuracy of 3D reconstruction.

The core ‌innovation lies in the network’s depth⁢ estimation, powered by a novel soft-edge ‌detector and an edge-matching module. Unlike traditional binary edge classification,⁤ this innovative approach ⁣treats edge⁣ detection in relief data as a multi-class problem. Recognizing ⁣that edges ​in relief ⁣images encompass⁤ not only brightness changes but‍ also variations in curvature, known as “soft edges,” the soft-edge detector analyzes the degree of “softness” present in these⁢ edges, ultimately leading to refined depth estimation.

The edge-matching ​module further strengthens this process. ‌By comparing soft-edge maps extracted ⁣from two ‍detectors with the depth⁣ map derived from the input relief⁢ photo, ‍the network ‌focuses its attention on soft-edge regions, resulting in even more accurate depth⁣ estimations.

the network optimizes a dynamic, edge-enhanced loss function that incorporates losses from all three tasks,‌ ultimately producing ⁤remarkably clear and detailed 3D reconstructions of these ancient reliefs.

You ⁢can delve deeper into⁤ the‍ intricacies of the team’s research by exploring their published paper. ​(Link​ to paper)
Interview Between ⁢Time.news Editor and Professor Satoshi Tanaka

Time.news Editor: Good morning, Professor Tanaka! Thank you‍ for joining​ us today. Your⁣ team’s recent achievement in resurrecting the hidden‌ relief sculpture at Borobudur Temple is nothing short of ‍fascinating. Can you ⁢start by ‌explaining what initially inspired this project?

Professor Satoshi Tanaka: ⁤Good morning!⁢ Thank you for having me. The ⁢inspiration came⁣ during our restoration studies of the Borobudur Temple, which is rich in history and artistry. We discovered that a significant piece of its heritage was lost, hidden beneath layers of earth.⁤ The challenge was to find a way to visualize and‍ reclaim this artwork, which ‌was only documented in⁣ a fleeting black-and-white photograph over ‍a​ century ago.

Time.news Editor: That’s ‍incredible! How did the application of​ AI play‌ a role in this undertaking?

Professor Satoshi Tanaka: ​ We leveraged a novel neural network ⁤specifically designed ⁣to interpret and reconstruct 3D models from 2D images. ⁢Traditional methods often miss the finer ​details due to depth compression,‍ as ⁤you ​mentioned, but our‌ new approach can‍ better handle complex‌ features like facial expressions and ornamentation, resulting in‍ a more ‌accurate digital representation of⁢ the relief.

Time.news Editor: It sounds like a⁣ significant leap forward. Can you tell us more about the limitations you encountered with your previous methods?

Professor Satoshi Tanaka: Certainly. Although our earlier technique achieved 95% ⁣reconstruction accuracy, it wasn’t able to fully capture the intricacies of ⁢relief sculptures. The flatness⁢ of 2D photographs made it difficult to discern⁣ subtle⁢ details, which​ are crucial for‍ historical accuracy and artistic‌ integrity. This new AI model has allowed us to overcome those shortcomings, ensuring that the revived piece⁢ truly reflects the original craftsmanship.

Time.news Editor: Reviving historical art using advanced technology is ‍a thrilling concept. What has been the reaction from the academic ‍community‍ and cultural heritage organizations regarding your findings?

Professor Satoshi Tanaka: ‌ The feedback has been overwhelmingly positive! Many scholars and heritage organizations see this method as a game-changer for archaeological studies. It opens ⁢up new⁢ avenues for preserving and interpreting cultural artifacts that⁢ may not ⁣be physically accessible. We hope⁣ it ​can serve as a model for​ similar projects worldwide.

Time.news Editor: Speaking of global implications, ⁤do‌ you ⁤envision this technology being applied elsewhere, perhaps in⁤ other historical sites?

Professor⁣ Satoshi Tanaka: Absolutely! This technology ⁢has broad applications. Any ​site with limited access to artifacts can benefit—whether it be for visualization, restoration, or educational purposes. We are already exploring partnerships in Egypt, Greece, and other parts of Asia to⁤ apply this method to their overlooked relics.

Time.news Editor: That’s exciting! Are there any ethical considerations you and your team⁢ have taken⁢ into account‍ while⁢ working on this project, especially related to ⁢cultural heritage?

Professor Satoshi Tanaka: ⁣ Yes, ethical‌ considerations are paramount in our⁣ work. We prioritize transparency and collaboration ​with local communities and​ cultural stakeholders.​ It’s ‌vital that ⁢the digital⁤ resurrection of artifacts is respectful to their significance⁤ and maintains⁢ a connection to their⁢ historical context. ⁤We wish⁣ to inform, ​not appropriate, their stories.

Time.news ⁤Editor: Wise words, Professor. ⁤what are your future plans ‌for your research team and this technology? Is there anything you’re particularly excited ⁣about?

Professor⁢ Satoshi Tanaka: We⁣ have⁢ some exciting plans! We aim to refine our AI​ models‌ further, enhancing our ability to reconstruct‌ even more complex historical artifacts. Additionally, we’re ⁢looking ‌to publish our findings in ‍a ‍broader context‌ to share our models and techniques with researchers globally. It’s an ⁤exciting time for digital humanities,⁤ and I’m eager to see where it leads!

Time.news Editor: ‌Thank you for sharing your insights, Professor ⁢Tanaka! Your work not only ⁣breathes life ‌into forgotten pieces ⁣of history but also paves the way for the future of ​cultural ⁣heritage preservation. We look forward to following your progress!

Professor Satoshi⁤ Tanaka: Thank you for the⁤ opportunity to discuss our work! I appreciate your interest, and I hope to share more exciting developments soon.

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