9 citations · 26 across the 17 of their papers we have counts for
17 papers
P2Voxel: Pyramid Pivot Voxelization for 3D Mesh Tokenization
Zhenhong Sun, Haozhe Liu, Yifu Wang +6
Triangle meshes provide explicit and accurate surface geometry, yet their irregular topology connectivity makes 3D mesh tokenization a geometric sampling problem: how to sample and…
I3DM: Implicit 3D-aware Memory Retrieval and Injection for Consistent Video Scene Generation
Jia Li, Han Yan, Yihang Chen +6
Despite remarkable progress in video generation, maintaining long-term scene consistency upon revisiting previously explored areas remains challenging. Existing solutions rely eith…
CDI3D: Cross-guided Dense-view Interpolation for 3D Reconstruction
Zhiyuan Wu, Xibin Song, Senbo Wang +8
3D object reconstruction from single-view image is a fundamental task in computer vision with wide-ranging applications. Recent advancements in Large Reconstruction Models (LRMs) h…
Pandora3D: A Comprehensive Framework for High-Quality 3D Shape and Texture Generation
Jiayu Yang, Taizhang Shang, Weixuan Sun +7
This report presents a comprehensive framework for generating high-quality 3D shapes and textures from diverse input prompts, including single images, multi-view images, and text d…
MARS: Mesh AutoRegressive Model for 3D Shape Detailization
Jingnan Gao, Weizhe Liu, Weixuan Sun +8
State-of-the-art methods for mesh detailization predominantly utilize Generative Adversarial Networks (GANs) to generate detailed meshes from coarse ones. These methods typically l…
BAG: Body-Aligned 3D Wearable Asset Generation
Zhongjin Luo, Yang Li, Mingrui Zhang +8
While recent advancements have shown remarkable progress in general 3D shape generation models, the challenge of leveraging these approaches to automatically generate wearable 3D a…
DoubleDiffusion: Combining Heat Diffusion with Denoising Diffusion for Texture Generation on 3D Meshes
Xuyang Wang, Ziang Cheng, Zhenyu Li +6
This paper addresses the problem of generating textures for 3D mesh assets. Existing approaches often rely on image diffusion models to generate multi-view image observations, whic…
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…
RGB-based Category-level Object Pose Estimation via Decoupled Metric Scale Recovery
Jiaxin Wei, Xibin Song, Weizhe Liu +3
While showing promising results, recent RGB-D camera-based category-level object pose estimation methods have restricted applications due to the heavy reliance on depth sensors. RG…
ConsistNet: Enforcing 3D Consistency for Multi-view Images Diffusion
Jiayu Yang, Ziang Cheng, Yunfei Duan +2
Given a single image of a 3D object, this paper proposes a novel method (named ConsistNet) that is able to generate multiple images of the same object, as if seen they are captured…