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most citedMotion-2-To-3: Leveraging 2D Motion Data for 3D Motion Generations

1 citations · 1 across the 7 of their papers we have counts for

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cs.CV2026

PointSplat: Compact Gaussian Splatting via Human-Centric Prediction

Yujie Guo, Yudong Jin, Lingteng Qiu +7

Producing 3D human representations from input views on the fly is essential for immersive live streaming systems, where representation compactness is as critical as high fidelity g…

cs.CV20261 cited

Motion-2-To-3: Leveraging 2D Motion Data for 3D Motion Generations

Ruoxi Guo, Huaijin Pi, Zehong Shen +8

Text-driven human motion synthesis has showcased its potential for revolutionizing motion design in the movie and game industry. Existing methods often rely on 3D motion capture da…

cs.CV2026

StreamingTalker: Audio-driven 3D Facial Animation with Autoregressive Diffusion Model

Yifan Yang, Zhi Cen, Sida Peng +6

This paper focuses on the task of speech-driven 3D facial animation, which aims to generate realistic and synchronized facial motions driven by speech inputs. Recent methods have e…

cs.CV2026

Scal3R: Scalable Test-Time Training for Large-Scale 3D Reconstruction

Tao Xie, Peishan Yang, Yudong Jin +8

This paper addresses the task of large-scale 3D scene reconstruction from long video sequences. Recent feed-forward reconstruction models have shown promising results by directly r…

cs.CV2026

Prompting Depth Anything for 4K Resolution Accurate Metric Depth Estimation

Haotong Lin, Sida Peng, Jingxiao Chen +7

Prompts play a critical role in unleashing the power of language and vision foundation models for specific tasks. For the first time, we introduce prompting into depth foundation m…

cs.CV2026

Mocap-2-to-3: Multi-view Lifting for Monocular Motion Recovery with 2D Pretraining

Zhumei Wang, Zechen Hu, Ruoxi Guo +5

Human motion recovery for real-world interaction demands both precise action details and metric-scale trajectories. Recovering absolute human pose from monocular input presents a v…