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20232026
most citedSMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation

29 citations · 30 across the 13 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.CV2025

Scaling Spatial Intelligence with Multimodal Foundation Models

Zhongang Cai, Ruisi Wang, Chenyang Gu +26

Despite remarkable progress, multimodal foundation models still exhibit surprising deficiencies in spatial intelligence. In this work, we explore scaling up multimodal foundation m…

cs.CV2025

The Quest for Generalizable Motion Generation: Data, Model, and Evaluation

Jing Lin, Ruisi Wang, Junzhe Lu +10

Despite recent advances in 3D human motion generation (MoGen) on standard benchmarks, existing text-to-motion models still face a fundamental bottleneck in their generalization cap…

cs.CV2025★ 1 cited

Holistic Evaluation of Multimodal LLMs on Spatial Intelligence

Zhongang Cai, Yubo Wang, Qingping Sun +21

Multimodal models have achieved remarkable progress in recent years. Nevertheless, they continue to exhibit notable limitations in spatial understanding and reasoning, the very cap…

cs.CV2025

ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization

Wenhao Shen, Wanqi Yin, Xiaofeng Yang +6

Human mesh recovery (HMR) from a single image is inherently ill-posed due to depth ambiguity and occlusions. Probabilistic methods have tried to solve this by generating numerous p…

cs.CV2025

SMPLest-X: Ultimate Scaling for Expressive Human Pose and Shape Estimation

Wanqi Yin, Zhongang Cai, Ruisi Wang +12

Expressive human pose and shape estimation (EHPS) unifies body, hands, and face motion capture with numerous applications. Despite encouraging progress, current state-of-the-art me…