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cs.CV2026

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.CV2026

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

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

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…

cs.CV2024

SMPLer-X: Scaling Up Expressive Human Pose and Shape Estimation

Zhongang Cai, Wanqi Yin, Ailing Zeng +10

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…