10 papers
Rosetta: Composable Native Multimodal Pretraining
Xiangyue Liu, Zijian Zhang, Miles Yang +3
Achieving true artificial general intelligence requires foundation models capable of integrating new modalities without forgetting prior knowledge. However, accommodating continuou…
Symbiotic-MoE: Unlocking the Synergy between Generation and Understanding
Xiangyue Liu, Zijian Zhang, Miles Yang +3
Empowering Large Multimodal Models (LMMs) with image generation often leads to catastrophic forgetting in understanding tasks due to severe gradient conflicts. While existing parad…
MeshFlow: Efficient Artistic Mesh Generation via MeshVAE and Flow-based Diffusion Transformer
Weiyu Li, Antoine Toisoul, Tom Monnier +4
We present MeshFlow, a new method for generating artist-like 3D meshes. Current mesh generators often adopt Auto-Regressive (AR) next-token prediction, a natural choice given the d…
AutoWeather4D: Autonomous Driving Video Weather Conversion via G-Buffer Dual-Pass Editing
Tianyu Liu, Weitao Xiong, Kunming Luo +4
Generative video models have significantly advanced the photorealistic synthesis of adverse weather for autonomous driving; however, they consistently demand massive datasets to le…
PoseMaster: A Unified 3D Native Framework for Stylized Pose Generation
Hongyu Yan, Kunming Luo, Weiyu Li +5
Pose stylization, which aims to synthesize stylized content aligning with target poses, serves as a fundamental task across 2D, 3D, and video domains. In the 3D realm, prevailing a…
SceneMaker: Open-set 3D Scene Generation with Decoupled De-occlusion and Pose Estimation Model
Yukai Shi, Weiyu Li, Zihao Wang +4
We propose a decoupled 3D scene generation framework called SceneMaker in this work. Due to the lack of sufficient open-set de-occlusion and pose estimation priors, existing method…