activity
20242026
collaborators

9 papers

cs.GR2026

Seed3D 2.0: Advancing High-Fidelity Simulation-Ready 3D Content Generation

Diandian Gu, Jing Lin, Gaohong Liu +25

We present Seed3D 2.0, an advanced 3D content generation system built on Seed3D 1.0, with substantial improvements across generation fidelity, simulation-ready capabilities, and ap…

eess.IV2026

X-LRM: X-ray Large Reconstruction Model for Extremely Sparse-View Computed Tomography Recovery in One Second

Guofeng Zhang, Ruyi Zha, Hao He +4

Sparse-view 3D CT reconstruction aims to recover volumetric structures from a limited number of 2D X-ray projections. Existing feedforward methods are constrained by the scarcity o…

cs.CV2025

Baking Gaussian Splatting into Diffusion Denoiser for Fast and Scalable Single-stage Image-to-3D Generation and Reconstruction

Yuanhao Cai, He Zhang, Kai Zhang +12

Existing feedforward image-to-3D methods mainly rely on 2D multi-view diffusion models that cannot guarantee 3D consistency. These methods easily collapse when changing the prompt…

cs.GR2025

CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refiner

Weiyu Li, Jiarui Liu, Hongyu Yan +5

We present a novel generative 3D modeling system, coined CraftsMan, which can generate high-fidelity 3D geometries with highly varied shapes, regular mesh topologies, and detailed…

cs.CV2025

LucidFusion: Reconstructing 3D Gaussians with Arbitrary Unposed Images

Hao He, Yixun Liang, Luozhou Wang +5

Recent large reconstruction models have made notable progress in generating high-quality 3D objects from single images. However, current reconstruction methods often rely on explic…

cs.CV2024

Multi-View Large Reconstruction Model via Geometry-Aware Positional Encoding and Attention

Mengfei Li, Xiaoxiao Long, Yixun Liang +6

Despite recent advancements in the Large Reconstruction Model (LRM) demonstrating impressive results, when extending its input from single image to multiple images, it exhibits ine…