@nobodyinperson@fosstodon.org2026-02-11 13:27:10
After a recent *terrible* first attempt at using matrix as communication platform for our rather big measurement campaign in summer, I just tried selfhosting Mattermost, and boy is it a smoother experience. It's as if it was made for team collaboration, funny eh 😅
Also my first time trying out nixos-containers, very nice to encapsulate or group services together independently of your host NixOS.
#Matrix
@hikingdude@mastodon.social2025-12-21 14:51:43
Now this was a gorgeous cycling loop. Temperature was around freezing but luckily just few wind. As you see, the weather was ace. Clouds and fog stayed in the north 🌞
Also tried Knee warmers, which was just right! A very good buy!
I just need a solution against freezing toes. @… ,I bought neoprene toe warmer! The shoes are just a bit tight then, …
@arXiv_csGR_bot@mastoxiv.page2026-02-02 08:48:10
EAG-PT: Emission-Aware Gaussians and Path Tracing for Indoor Scene Reconstruction and Editing
Xijie Yang, Mulin Yu, Changjian Jiang, Kerui Ren, Tao Lu, Jiangmiao Pang, Dahua Lin, Bo Dai, Linning Xu
https://arxiv.org/abs/2601.23065 https://arxiv.org/pdf/2601.23065 https://arxiv.org/html/2601.23065
arXiv:2601.23065v1 Announce Type: new
Abstract: Recent reconstruction methods based on radiance field such as NeRF and 3DGS reproduce indoor scenes with high visual fidelity, but break down under scene editing due to baked illumination and the lack of explicit light transport. In contrast, physically based inverse rendering relies on mesh representations and path tracing, which enforce correct light transport but place strong requirements on geometric fidelity, becoming a practical bottleneck for real indoor scenes. In this work, we propose Emission-Aware Gaussians and Path Tracing (EAG-PT), aiming for physically based light transport with a unified 2D Gaussian representation. Our design is based on three cores: (1) using 2D Gaussians as a unified scene representation and transport-friendly geometry proxy that avoids reconstructed mesh, (2) explicitly separating emissive and non-emissive components during reconstruction for further scene editing, and (3) decoupling reconstruction from final rendering by using efficient single-bounce optimization and high-quality multi-bounce path tracing after scene editing. Experiments on synthetic and real indoor scenes show that EAG-PT produces more natural and physically consistent renders after editing than radiant scene reconstructions, while preserving finer geometric detail and avoiding mesh-induced artifacts compared to mesh-based inverse path tracing. These results suggest promising directions for future use in interior design, XR content creation, and embodied AI.
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