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Forge4D model enables rapid 4D human reconstruction from video

Researchers have introduced Forge4D, a novel feed-forward model designed for rapid 4D human reconstruction and interpolation from uncalibrated video footage. This model addresses limitations in existing methods by enabling both novel view and novel time synthesis, simplifying the process into a joint task of streaming 3D Gaussian reconstruction and dense motion prediction. Forge4D utilizes learnable state tokens for temporal consistency and a self-supervised retargeting loss for motion prediction, demonstrating effectiveness across various datasets. AI

IMPACT This research could accelerate applications requiring real-time 3D human modeling from video, such as in virtual reality and animation.

RANK_REASON The cluster contains an arXiv preprint detailing a new method for 4D human reconstruction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Forge4D model enables rapid 4D human reconstruction from video

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The cluster contains an arXiv preprint detailing a new method for 4D human reconstruction. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Yingdong Hu, Yisheng He, Jinnan Chen, Weihao Yuan, Kejie Qiu, Zehong Lin, Siyu Zhu, Zilong Dong, Steven Hoi, Jun Zhang ·

    Forge4D: Feed-Forward 4D Human Reconstruction and Interpolation from Uncalibrated Sparse-view Videos

    arXiv:2509.24209v2 Announce Type: replace Abstract: Instant reconstruction of dynamic 3D humans from uncalibrated sparse-view videos is critical for numerous downstream applications. Existing methods, however, are either limited by the slow reconstruction speeds or incapable of g…