4 papers
MUSE: A Multi-agent Framework for Unconstrained Story Envisioning via Closed-Loop Cognitive Orchestration
Wenzhang Sun, Zhenyu Wang, Zhangchi Hu +3
Generating long-form audio-visual stories from a short user prompt remains challenging due to an intent-execution gap, where high-level narrative intent must be preserved across co…
DeCo-VAE: Learning Compact Latents for Video Reconstruction via Decoupled Representation
Xiangchen Yin, Jiahui Yuan, Zhangchi Hu +5
Existing video Variational Autoencoders (VAEs) generally overlook the similarity between frame contents, leading to redundant latent modeling. In this paper, we propose decoupled V…
DrivingScene: A Multi-Task Online Feed-Forward 3D Gaussian Splatting Method for Dynamic Driving Scenes
Qirui Hou, Wenzhang Sun, Chang Zeng +3
Real-time, high-fidelity reconstruction of dynamic driving scenes is challenged by complex dynamics and sparse views, with prior methods struggling to balance quality and efficienc…
PAGS: Priority-Adaptive Gaussian Splatting for Dynamic Driving Scenes
Ying A, Wenzhang Sun, Chang Zeng +3
Reconstructing dynamic 3D urban scenes is crucial for autonomous driving, yet current methods face a stark trade-off between fidelity and computational cost. This inefficiency stem…