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20242026
most citedLHM: Large Animatable Human Reconstruction Model from a Single Image in Seconds

1 citations · 2 across the 5 of their papers we have counts for

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cs.CV2026

Glob3R: Global Structure-from-Motion with 3D Foundation Models

Junyuan Deng, Heng Li, Kejie Qiu +7

Recent 3D geometric foundation models, such as VGGT, provide robust feed-forward 3D reconstruction by directly predicting camera poses and 3D scene points from input images. Howeve…

cs.CV2025

OmniMotion: Multimodal Motion Generation with Continuous Masked Autoregression

Zhe Li, Weihao Yuan, Weichao Shen +3

Whole-body multi-modal human motion generation poses two primary challenges: creating an effective motion generation mechanism and integrating various modalities, such as text, spe…

cs.CV2025★ 1 cited

LHM: Large Animatable Human Reconstruction Model from a Single Image in Seconds

Lingteng Qiu, Xiaodong Gu, Peihao Li +8

Animatable 3D human reconstruction from a single image is a challenging problem due to the ambiguity in decoupling geometry, appearance, and deformation. Recent advances in 3D huma…

cs.CV2024

LaMP: Language-Motion Pretraining for Motion Generation, Retrieval, and Captioning

Zhe Li, Weihao Yuan, Yisheng He +7

Language plays a vital role in the realm of human motion. Existing methods have largely depended on CLIP text embeddings for motion generation, yet they fall short in effectively a…

cs.CV2024★ 1 cited

MoGenTS: Motion Generation based on Spatial-Temporal Joint Modeling

Weihao Yuan, Weichao Shen, Yisheng He +5

Motion generation from discrete quantization offers many advantages over continuous regression, but at the cost of inevitable approximation errors. Previous methods usually quantiz…