1 citations · 1 across the 10 of their papers we have counts for
13 papers
MeshOctave: Vertex Split-and-Rewire Cascades for Native Mesh Generation
Junkai Lin, Tianhao Zhao, Hang Long +10
Generating compact, artist-style meshes with explicit topology typically relies on autoregressive models which incur prohibitive sequential per-token costs, or continuous flow mode…
Meshy T2: Fast Native Mesh Generation with Flow Matching
Jiale Xu, Rendong Liang, Yuhao Long +5
Polygonal meshes are the standard surface representation of modern 3D pipelines, and generating high-quality meshes with artist-style topology is essential for film, gaming, and in…
LATO.2: Factorized 3D Mesh Generation with Vertex and Topology Flow
Hang Long, Tianhao Zhao, Junkai Lin +8
Flow matching over carefully designed latent representations has recently emerged as a powerful paradigm for topology-aware mesh generation. Existing approaches, however, model ver…
MeshWeaver: Sparse-Voxel-Guided Surface Weaving for Autoregressive Mesh Generation
Jiale Xu, Wang Zhao, Ying Shan
Autoregressive mesh generation has gained attention by tokenizing meshes into sequences and training models in a language-modeling fashion. However, existing approaches suffer from…
Sculpt4D: Generating 4D Shapes via Sparse-Attention Diffusion Transformers
Minghao Yin, Wenbo Hu, Jiale Xu +2
Recent breakthroughs in 3D generative modeling have yielded remarkable progress in static shape synthesis, yet high-fidelity dynamic 4D generation remains elusive, hindered by temp…
Rolling Forcing: Autoregressive Long Video Diffusion in Real Time
Kunhao Liu, Wenbo Hu, Jiale Xu +2
Streaming video generation, as one fundamental component in interactive world models and neural game engines, aims to generate high-quality, low-latency, and temporally coherent lo…
DepthSync: Diffusion Guidance-Based Depth Synchronization for Scale- and Geometry-Consistent Video Depth Estimation
Yue-Jiang Dong, Wang Zhao, Jiale Xu +2
Diffusion-based video depth estimation methods have achieved remarkable success with strong generalization ability. However, predicting depth for long videos remains challenging. E…
IC-Custom: Diverse Image Customization via In-Context Learning
Yaowei Li, Xiaoyu Li, Zhaoyang Zhang +11
Image customization, a crucial technique for industrial media production, aims to generate content that is consistent with reference images. However, current approaches conventiona…
Assembler: Scalable 3D Part Assembly via Anchor Point Diffusion
Wang Zhao, Yan-Pei Cao, Jiale Xu +2
We present Assembler, a scalable and generalizable framework for 3D part assembly that reconstructs complete objects from input part meshes and a reference image. Unlike prior appr…
DI-PCG: Diffusion-based Efficient Inverse Procedural Content Generation for High-quality 3D Asset Creation
Wang Zhao, Yan-Pei Cao, Jiale Xu +2
Procedural Content Generation (PCG) is powerful in creating high-quality 3D contents, yet controlling it to produce desired shapes is difficult and often requires extensive paramet…
NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images
Lingen Li, Zhaoyang Zhang, Yaowei Li +7
Recent advancements in generative models have significantly improved novel view synthesis (NVS) from multi-view data. However, existing methods depend on external multi-view alignm…
FreeSplatter: Pose-free Gaussian Splatting for Sparse-view 3D Reconstruction
Jiale Xu, Shenghua Gao, Ying Shan
Sparse-view reconstruction models typically require precise camera poses, yet obtaining these parameters from sparse-view images remains challenging. We introduce FreeSplatter, a s…
NovelGS: Consistent Novel-view Denoising via Large Gaussian Reconstruction Model
Jinpeng Liu, Jiale Xu, Weihao Cheng +4
We introduce NovelGS, a diffusion model for Gaussian Splatting (GS) given sparse-view images. Recent works leverage feed-forward networks to generate pixel-aligned Gaussians, which…