7 papers
PointNet4D: A Lightweight 4D Point Cloud Video Backbone for Online and Offline Perception in Robotic Applications
Yunze Liu, Zifan Wang, Peiran Wu +1
Understanding dynamic 4D environments-3D space evolving over time-is critical for robotic and interactive systems. These applications demand systems that can process streaming poin…
OnlineHOI: Towards Online Human-Object Interaction Generation and Perception
Yihong Ji, Yunze Liu, Yiyao Zhuo +4
The perception and generation of Human-Object Interaction (HOI) are crucial for fields such as robotics, AR/VR, and human behavior understanding. However, current approaches model…
UGC-VideoCaptioner: An Omni UGC Video Detail Caption Model and New Benchmarks
Peiran Wu, Yunze Liu, Zhengdong Zhu +2
Real-world user-generated videos, especially on platforms like TikTok, often feature rich and intertwined audio visual content. However, existing video captioning benchmarks and mo…
MutualNeRF: Improve the Performance of NeRF under Limited Samples with Mutual Information Theory
Zifan Wang, Jingwei Li, Yitang Li +1
This paper introduces MutualNeRF, a framework enhancing Neural Radiance Field (NeRF) performance under limited samples using Mutual Information Theory. While NeRF excels in 3D scen…
ST-Think: How Multimodal Large Language Models Reason About 4D Worlds from Ego-Centric Videos
Peiran Wu, Yunze Liu, Miao Liu +1
Humans excel at spatial-temporal reasoning, effortlessly interpreting dynamic visual events from an egocentric viewpoint. However, whether multimodal large language models (MLLMs)…
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…