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Junzhe Lu

3 accepted papers

2026

EchoMotion: Unified Human Video and Motion Generation via Dual-Modality Diffusion Transformer

ICLR 2026poster

Video generation models have advanced significantly, yet they still struggle to synthesize complex human movements due to the high degrees of freedom in human articulation. This limitation stems from the intrinsic constraints of pixel-only training objectives, which inherently bias models toward app…

Cited by 0SourceScholar
2026

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

ICLR 2026poster

Despite recent advances in 3D human motion generation (MoGen) on standard benchmarks, existing models still face a fundamental bottleneck in their generalization capability. In contrast, adjacent generative fields, most notably video generation (ViGen), have demonstrated remarkable generalization in…

Cited by 0SourcecodeScholar
2025

DPoser-X: Diffusion Model as Robust 3D Whole-body Human Pose Prior

ICCV 2025poster

We present DPoser-X, a diffusion-based prior model for 3D whole-body human poses. Building a versatile and robust full-body human pose prior remains challenging due to the inherent complexity of articulated human poses and the scarcity of high-quality whole-body pose datasets. To address these limit…

Cited by 0SourcePDFScholar