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RepWAM: World Action Modeling with Representation Visual-Action Tokenizers
Junke Wang, Qihang Zhang, Shuai Yang +5
This work presents RepWAM, a representation-centric world action model (WAM) built on representation visual-action tokenizers. Existing WAMs typically inherit reconstruction-orient…
Video World Models with Long-term Spatial Memory
Tong Wu, Shuai Yang, Ryan Po +4
Emerging world models autoregressively generate video frames in response to actions, such as camera movements and text prompts, among other control signals. Due to limited temporal…
OmniCam: Unified Multimodal Video Generation via Camera Control
Xiaoda Yang, Jiayang Xu, Kaixuan Luan +9
Camera control, which achieves diverse visual effects by changing camera position and pose, has attracted widespread attention. However, existing methods face challenges such as co…
Imagine360: Immersive 360 Video Generation from Perspective Anchor
Jing Tan, Shuai Yang, Tong Wu +4
videos offer a hyper-immersive experience that allows the viewers to explore a dynamic scene from full 360 degrees. To achieve more user-friendly and personalized conte…
MMScan: A Multi-Modal 3D Scene Dataset with Hierarchical Grounded Language Annotations
Ruiyuan Lyu, Jingli Lin, Tai Wang +8
With the emergence of LLMs and their integration with other data modalities, multi-modal 3D perception attracts more attention due to its connectivity to the physical world and mak…
Grounded 3D-LLM with Referent Tokens
Yilun Chen, Shuai Yang, Haifeng Huang +5
Prior studies on 3D scene understanding have primarily developed specialized models for specific tasks or required task-specific fine-tuning. In this study, we propose Grounded 3D-…