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Survey details 4D representation advances in AI-driven graphics

A new survey paper explores the rapidly advancing field of 4D generation and reconstruction, focusing on how 3D geometry evolves over time with motion and interaction. The paper highlights representative works rather than an exhaustive list, aiming to guide readers in selecting and customizing appropriate 4D representations for their specific tasks. It covers popular methods like NeRFs and 3D Gaussian Splatting, alongside less-explored areas such as structured models and long-range motions, while also discussing the role and limitations of large language models and video foundational models in this domain. AI

RANK_REASON The cluster contains an academic survey paper on a specific subfield of computer graphics and AI. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.CV →

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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Mingrui Zhao, Sauradip Nag, Kai Wang, Aditya Vora, Guangda Ji, Peter Chun, Ali Mahdavi-Amiri, Hao Zhang ·

    Advances in 4D Representation: Geometry, Motion, and Interaction

    arXiv:2510.19255v3 Announce Type: replace Abstract: We present a survey on 4D generation and reconstruction, a fast-evolving subfield of computer graphics whose developments have been propelled by recent advances in neural fields, geometric and motion deep learning, as well as 3D…