5 papers
TACO: Taming Diffusion for in-the-wild Video Amodal Completion
Ruijie Lu, Yixin Chen, Yu Liu +5
Humans can infer complete shapes and appearances of objects from limited visual cues, relying on extensive prior knowledge of the physical world. However, completing partially obse…
DreamArt: Generating Interactable Articulated Objects from a Single Image
Ruijie Lu, Yu Liu, Jiaxiang Tang +6
Generating articulated objects, such as laptops and microwaves, is a crucial yet challenging task with extensive applications in Embodied AI and AR/VR. Current image-to-3D methods…
MOVIS: Enhancing Multi-Object Novel View Synthesis for Indoor Scenes
Ruijie Lu, Yixin Chen, Junfeng Ni +5
Repurposing pre-trained diffusion models has been proven to be effective for NVS. However, these methods are mostly limited to a single object; directly applying such methods to co…
Template-free Articulated Gaussian Splatting for Real-time Reposable Dynamic View Synthesis
Diwen Wan, Yuxiang Wang, Ruijie Lu +1
While novel view synthesis for dynamic scenes has made significant progress, capturing skeleton models of objects and re-posing them remains a challenging task. To tackle this prob…
Superpoint Gaussian Splatting for Real-Time High-Fidelity Dynamic Scene Reconstruction
Diwen Wan, Ruijie Lu, Gang Zeng
Rendering novel view images in dynamic scenes is a crucial yet challenging task. Current methods mainly utilize NeRF-based methods to represent the static scene and an additional t…