1 citations · 2 across the 10 of their papers we have counts for
13 papers
Ring Forcing: Towards Precise Long-Term Memory for Autoregressive Video Diffusion
Bowen Xue, Brandon Y. Feng, Chenguo Lin +6
Scaling video generation to long durations reveals a critical bottleneck: current models lack robust long-term memory. This deficiency can be studied along two critical aspects: ob…
4DStreamCtrl: Interactive Video Generation with Online 4D Control
Shiqian Li, Chenguo Lin, Zhiguang Liu +4
Generative video models now synthesize footage nearly indistinguishable from reality. Their promise as interactive tools hinges on fine-grained control of how objects and the camer…
GEAR: Guided End-to-End AutoRegression for Image Synthesis
Bin Lin, Zheyuan Liu, Chenguo Lin +8
Visual generative models are typically trained in two stages. A tokenizer is first trained for reconstruction and then frozen, after which a generator is trained on its discrete in…
ID-Crafter: VLM-Grounded Online RL for Compositional Multi-Subject Video Generation
Panwang Pan, Jingjing Zhao, Yuchen Lin +5
Significant progress has been achieved in high-fidelity video synthesis, yet current paradigms often fall short in effectively integrating identity information from multiple subjec…
DynamicVerse: A Physically-Aware Multimodal Framework for 4D World Modeling
Kairun Wen, Yuzhi Huang, Runyu Chen +16
Understanding the dynamic physical world, characterized by its evolving 3D structure, real-world motion, and semantic content with textual descriptions, is crucial for human-agent…
Diff4Splat: Controllable 4D Scene Generation with Latent Dynamic Reconstruction Models
Panwang Pan, Chenguo Lin, Jingjing Zhao +8
We introduce Diff4Splat, a feed-forward method that synthesizes controllable and explicit 4D scenes from a single image. Our approach unifies the generative priors of video diffusi…
MoVieS: Motion-Aware 4D Dynamic View Synthesis in One Second
Chenguo Lin, Yuchen Lin, Panwang Pan +5
We present MoVieS, a Motion-aware View Synthesis model that reconstructs 4D dynamic scenes from monocular videos in one second. It represents dynamic 3D scenes with pixel-aligned G…
PartCrafter: Structured 3D Mesh Generation via Compositional Latent Diffusion Transformers
Yuchen Lin, Chenguo Lin, Panwang Pan +4
We introduce PartCrafter, the first structured 3D generative model that jointly synthesizes multiple semantically meaningful and geometrically distinct 3D meshes from a single RGB…
OmniPhysGS: 3D Constitutive Gaussians for General Physics-Based Dynamics Generation
Yuchen Lin, Chenguo Lin, Jianjin Xu +1
Recently, significant advancements have been made in the reconstruction and generation of 3D assets, including static cases and those with physical interactions. To recover the phy…
DiffSplat: Repurposing Image Diffusion Models for Scalable Gaussian Splat Generation
Chenguo Lin, Panwang Pan, Bangbang Yang +2
Recent advancements in 3D content generation from text or a single image struggle with limited high-quality 3D datasets and inconsistency from 2D multi-view generation. We introduc…
InstructLayout: Instruction-Driven 2D and 3D Layout Synthesis with Semantic Graph Prior
Chenguo Lin, Yuchen Lin, Panwang Pan +2
Comprehending natural language instructions is a charming property for both 2D and 3D layout synthesis systems. Existing methods implicitly model object joint distributions and exp…
HumanSplat: Generalizable Single-Image Human Gaussian Splatting with Structure Priors
Panwang Pan, Zhuo Su, Chenguo Lin +6
Despite recent advancements in high-fidelity human reconstruction techniques, the requirements for densely captured images or time-consuming per-instance optimization significantly…
InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior
Chenguo Lin, Yadong Mu
Comprehending natural language instructions is a charming property for 3D indoor scene synthesis systems. Existing methods directly model object joint distributions and express obj…