9 citations · 26 across the 17 of their papers we have counts for
8 papers · 1 filter
T-S2S: Training-free Triplet Tuning for Sketch to Scene Synthesis in Controllable Concept Art Generation
Zhenhong Sun, Yifu Wang, Yonhon Ng +4
2D concept art generation for 3D scenes is a crucial yet challenging task in computer graphics, as creating natural intuitive environments still demands extensive manual effort in…
PhyCAGE: Physically Plausible Compositional 3D Asset Generation from a Single Image
Han Yan, Mingrui Zhang, Yang Li +2
We present PhyCAGE, the first approach for physically plausible compositional 3D asset generation from a single image. Given an input image, we first generate consistent multi-view…
Prim2Room: Layout-Controllable Room Mesh Generation from Primitives
Chengzeng Feng, Jiacheng Wei, Cheng Chen +5
We propose Prim2Room, a novel framework for controllable room mesh generation leveraging 2D layout conditions and 3D primitive retrieval to facilitate precise 3D layout specificati…
Sketch2Scene: Automatic Generation of Interactive 3D Game Scenes from User's Casual Sketches
Yongzhi Xu, Yonhon Ng, Yifu Wang +6
3D Content Generation is at the heart of many computer graphics applications, including video gaming, film-making, virtual and augmented reality, etc. This paper proposes a novel d…
LAM3D: Large Image-Point-Cloud Alignment Model for 3D Reconstruction from Single Image
Ruikai Cui, Xibin Song, Weixuan Sun +8
Large Reconstruction Models have made significant strides in the realm of automated 3D content generation from single or multiple input images. Despite their success, these models…
NeuSDFusion: A Spatial-Aware Generative Model for 3D Shape Completion, Reconstruction, and Generation
Ruikai Cui, Weizhe Liu, Weixuan Sun +9
3D shape generation aims to produce innovative 3D content adhering to specific conditions and constraints. Existing methods often decompose 3D shapes into a sequence of localized c…
Frankenstein: Generating Semantic-Compositional 3D Scenes in One Tri-Plane
Han Yan, Yang Li, Zhennan Wu +9
We present Frankenstein, a diffusion-based framework that can generate semantic-compositional 3D scenes in a single pass. Unlike existing methods that output a single, unified 3D s…
BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane Extrapolation
Zhennan Wu, Yang Li, Han Yan +8
We present BlockFusion, a diffusion-based model that generates 3D scenes as unit blocks and seamlessly incorporates new blocks to extend the scene. BlockFusion is trained using dat…