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20242026
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cs.CV2026

Multi-scale Coarse-to-fine Modeling for Test-time Human Motion Control

Nhat Le, Daochang Liu, Anh Nguyen +1

We present MSCoT, a multi-scale, coarse-to-fine model for test-time human motion synthesis and control. Unlike recent approaches that rely on multiple iterative denoising/token-pre…

cs.CV2026

Diffusion Masked Pretraining for Dynamic Point Cloud

Zhuoyue Zhang, Jihua Zhu, Chaowei Fang +2

Dynamic point cloud pretraining is still dominated by masked reconstruction objectives. However, these objectives inherit two key limitations. Existing methods inject ground-truth…

cs.CV2026

Mantis: Mamba-native Tuning is Efficient for 3D Point Cloud Foundation Models

Zihao Guo, Jihua Zhu, Jian Liu +1

Pre-trained 3D point cloud foundation models (PFMs) have demonstrated strong transferability across diverse downstream tasks. However, full fine-tuning these models is computationa…

cs.CV2026

GenHOI: Generalized Hand-Object Pose Estimation with Occlusion Awareness

Hui Yang, Wei Sun, Jian Liu +6

Generalized 3D hand-object pose estimation from a single RGB image remains challenging due to the large variations in object appearances and interaction patterns, especially under…

cs.CV2026

Class-Partitioned VQ-VAE and Latent Flow Matching for Point Cloud Scene Generation

Dasith de Silva Edirimuni, Ajmal Saeed Mian

Most 3D scene generation methods are limited to only generating object bounding box parameters while newer diffusion methods also generate class labels and latent features. Using o…

cs.CV2025

ARMFlow: AutoRegressive MeanFlow for Online 3D Human Reaction Generation

Zichen Geng, Zeeshan Hayder, Wei Liu +2

3D human reaction generation faces three main challenges:(1) high motion fidelity, (2) real-time inference, and (3) autoregressive adaptability for online scenarios. Existing metho…