12 papers
Seedance 2.0: Advancing Video Generation for World Complexity
Team Seedance, De Chen, Liyang Chen +168
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…
SceneAssistant: A Visual Feedback Agent for Open-Vocabulary 3D Scene Generation
Jun Luo, Jiaxiang Tang, Ruijie Lu +1
Text-to-3D scene generation from natural language is highly desirable for digital content creation. However, existing methods are largely domain-restricted or reliant on predefined…
G4Splat: Geometry-Guided Gaussian Splatting with Generative Prior
Junfeng Ni, Yixin Chen, Zhifei Yang +4
Despite recent advances in leveraging generative prior from pre-trained diffusion models for 3D scene reconstruction, existing methods still face two critical limitations. First, d…
GaussianFluent: Gaussian Simulation for Dynamic Scenes with Mixed Materials
Bei Huang, Yixin Chen, Ruijie Lu +4
3D Gaussian Splatting (3DGS) has emerged as a prominent 3D representation for high-fidelity and real-time rendering. Prior work has coupled physics simulation with Gaussians, but p…
VideoArtGS: Building Digital Twins of Articulated Objects from Monocular Video
Yu Liu, Baoxiong Jia, Ruijie Lu +5
Building digital twins of articulated objects from monocular video presents an essential challenge in computer vision, which requires simultaneous reconstruction of object geometry…
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…