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cs.CV2025

VideoMAP: Toward Scalable Mamba-based Video Autoregressive Pretraining

Yunze Liu, Peiran Wu, Cheng Liang +3

Recent Mamba-based architectures for video understanding demonstrate promising computational efficiency and competitive performance, yet struggle with overfitting issues that hinde…

cs.CV2024

MAP: Unleashing Hybrid Mamba-Transformer Vision Backbone's Potential with Masked Autoregressive Pretraining

Yunze Liu, Li Yi

Hybrid Mamba-Transformer networks have recently garnered broad attention. These networks can leverage the scalability of Transformers while capitalizing on Mamba's strengths in lon…

cs.CV2024

Physics-aware Hand-object Interaction Denoising

Haowen Luo, Yunze Liu, Li Yi

The credibility and practicality of a reconstructed hand-object interaction sequence depend largely on its physical plausibility. However, due to high occlusions during hand-object…

cs.CV2024

CrossVideo: Self-supervised Cross-modal Contrastive Learning for Point Cloud Video Understanding

Yunze Liu, Changxi Chen, Zifan Wang +1

This paper introduces a novel approach named CrossVideo, which aims to enhance self-supervised cross-modal contrastive learning in the field of point cloud video understanding. Tra…

cs.CV2023

Interactive Humanoid: Online Full-Body Motion Reaction Synthesis with Social Affordance Canonicalization and Forecasting

Yunze Liu, Changxi Chen, Li Yi

We focus on the human-humanoid interaction task optionally with an object. We propose a new task named online full-body motion reaction synthesis, which generates humanoid reaction…

cs.CV20231 cited

NSM4D: Neural Scene Model Based Online 4D Point Cloud Sequence Understanding

Yuhao Dong, Zhuoyang Zhang, Yunze Liu +1

Understanding 4D point cloud sequences online is of significant practical value in various scenarios such as VR/AR, robotics, and autonomous driving. The key goal is to continuousl…