TL;DR
This paper introduces a data-free neural mesh inpainting framework that operates directly on incomplete input meshes while preserving the original mesh connectivity in a self-supervised graph convolutional network.
This work proposes TopoSurfel, a novel framework that closes the loop between Gaussian surfels and continuous meshes, and introduces a mesh-guided surfel evolution strategy, including normal alignment and geometry-aware density control, to effectively suppress floaters and fill surface holes.
Inpainting 3D Gaussian Splatting scenes, a key challenge in 3D editing, requires generating plausible content within a masked region of 3D space. Prior approaches rely on 2D diffusion models to produce one or several inpainted reference views, making them susceptible to challenges associated with multi-view inconsisten...
Advances in neural rendering have enabled high-fidelity multi-view reconstruction of 3D scenes. However, free-form non-rigid shape editing remains a significant challenge. Point-based neural representations are highly desirable for multi-view reconstruction because they lack fixed connectivity, which does not constrain...
A vertex-based deformation optimization quantity capable of large deformations and robustness to such noise is proposed, periodically remesh using an isotropic remesher that interpolates and carries forward the deformation optimization state.
3D content generation technology has significantly advanced the work of designers, as well as the 3D printing and gaming industries. However, it remains difficult to produce lightweight, editable, and topologically clean artistic content that is directly production-ready. To achieve this, we present TaoFlowForge, an ar...
This work proposes a decompose-before-reconstruct approach, which significantly improves mesh fidelity and novel-view synthesis and novel-view synthesis, while supporting object-wise modifiability and interactivity.
A cross-section of the MIT community convened discussions on topics ranging from data centers and super pollutants to agriculture and education.
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
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