Tootfinder

Omg, #immich just told me that we visited #rome 12 years ago. 12?! Omg - where does time go?
But I'm just - so - glad that I took those photos. And for this feature in Immich.
These reminders about our vacations and adventures.. Just so precious.

Finnisharchitecture.fi | Homepage
https://www.finnisharchitecture.fi/

Homepage
This curated database brings together historical landmarks, iconic modern masterpieces, and a broad spectrum of contemporary architecture that form the…

David Loggan spent 12 years sketching & engraving the town & colleges of Cambridge before publishing his book of plates in 1690 as 'Cantabrigia Illustrata'. Background: https://www.museumofcambridge.org.uk/2025/10/david-loggans-views-of-ca…

David Loggan’s views of Cambridge: An extraordinary visual testimony of 17th century Cambridge
By Dr N. Henry The Museum of Cambridge has on display, on the first floor, an antique print of David Loggan’s views of Cambridge from the east and the west. This print was once part of Cantabrigia …

[Man beachte das Foto mit dem Affen]
https://www.nytimes.com/2026/02/06/business/the-taj-story-conspiracy-taj-mahal-hindu.html?unlocked_article_code=1.KFA.Sksu.OEEyaI0qByzv&smid=url…

An Indian Film Embraces a Taj Majal Conspiracy Theory
The internet and a new film have breathed life into old conspiracy theories about one of the world’s most famous landmarks.

Genus-0 Surface Parameterization using Spherical Beltrami Differentials
Zhehao Xu, Lok Ming Lui
https://arxiv.org/abs/2602.01589 https://arxiv.org/pdf/2602.01589 https://arxiv.org/html/2602.01589
arXiv:2602.01589v1 Announce Type: new
Abstract: Spherical surface parameterization is a fundamental tool in geometry processing and imaging science. For a genus-0 closed surface, many efficient algorithms can map the surface to the sphere; consequently, a broad class of task-driven genus-0 mapping problems can be reduced to constructing a high-quality spherical self-map. However, existing approaches often face a trade-off between satisfying task objectives (e.g., landmark or feature alignment), maintaining bijectivity, and controlling geometric distortion. We introduce the Spherical Beltrami Differential (SBD), a two-chart representation of quasiconformal self-maps of the sphere, and establish its correspondence with spherical homeomorphisms up to conformal automorphisms. Building on the Spectral Beltrami Network (SBN), we propose a neural optimization framework BOOST that optimizes two Beltrami fields on hemispherical stereographic charts and enforces global consistency through explicit seam-aware constraints. Experiments on large-deformation landmark matching and intensity-based spherical registration demonstrate the effectiveness of our proposed framework. We further apply the method to brain cortical surface registration, aligning sulcal landmarks and jointly matching cortical sulci depth maps, showing improved task fidelity with controlled distortion and robust bijective behavior.
toXiv_bot_toot