28 citations · 88 across the 18 of their papers we have counts for
14 papers · 1 filter
Hitem3D 2.0: Multi-View Guided Native 3D Texture Generation
Huiang He, Shengchu Zhao, Jianwen Huang +7
Although recent advances have improved the quality of 3D texture generation, existing methods still struggle with incomplete texture coverage, cross-view inconsistency, and misalig…
EI-Part: Explode for Completion and Implode for Refinement
Wanhu Sun, Zhongjin Luo, Heliang Zheng +6
Part-level 3D generation is crucial for various downstream applications, including gaming, film production, and industrial design. However, decomposing a 3D shape into geometricall…
Know3D: Prompting 3D Generation with Knowledge from Vision-Language Models
Wenyue Chen, Wenjue Chen, Peng Li +6
Recent advances in 3D generation have improved the fidelity and geometric details of synthesized 3D assets. However, due to the inherent ambiguity of single-view observations and t…
Topology-Preserved Auto-regressive Mesh Generation in the Manner of Weaving Silk
Gaochao Song, Zibo Zhao, Haohan Weng +3
Existing auto-regressive mesh generation approaches suffer from ineffective topology preservation, which is crucial for practical applications. This limitation stems from previous…
Hyper3D: Efficient 3D Representation via Hybrid Triplane and Octree Feature for Enhanced 3D Shape Variational Auto-Encoders
Jingyu Guo, Sensen Gao, Jia-Wang Bian +4
Recent 3D content generation pipelines often leverage Variational Autoencoders (VAEs) to encode shapes into compact latent representations, facilitating diffusion-based generation.…
NeuDA: Neural Deformable Anchor for High-Fidelity Implicit Surface Reconstruction
Bowen Cai, Jinchi Huang, Rongfei Jia +2
This paper studies implicit surface reconstruction leveraging differentiable ray casting. Previous works such as IDR and NeuS overlook the spatial context in 3D space when predicti…
3D Scene Creation and Rendering via Rough Meshes: A Lighting Transfer Avenue
Bowen Cai, Yujie Li, Yuqin Liang +4
This paper studies how to flexibly integrate reconstructed 3D models into practical 3D modeling pipelines such as 3D scene creation and rendering. Due to the technical difficulty,…
DCCF: Deep Comprehensible Color Filter Learning Framework for High-Resolution Image Harmonization
Ben Xue, Shenghui Ran, Quan Chen +3
Image color harmonization algorithm aims to automatically match the color distribution of foreground and background images captured in different conditions. Previous deep learning…
Ray Priors through Reprojection: Improving Neural Radiance Fields for Novel View Extrapolation
Jian Zhang, Yuanqing Zhang, Huan Fu +6
Neural Radiance Fields (NeRF) have emerged as a potent paradigm for representing scenes and synthesizing photo-realistic images. A main limitation of conventional NeRFs is that the…
Modeling Indirect Illumination for Inverse Rendering
Yuanqing Zhang, Jiaming Sun, Xingyi He +3
Recent advances in implicit neural representations and differentiable rendering make it possible to simultaneously recover the geometry and materials of an object from multi-view R…
Exploiting Diverse Characteristics and Adversarial Ambivalence for Domain Adaptive Segmentation
Bowen Cai, Huan Fu, Rongfei Jia +3
Adapting semantic segmentation models to new domains is an important but challenging problem. Recently enlightening progress has been made, but the performance of existing methods…
3D-FRONT: 3D Furnished Rooms with layOuts and semaNTics
Huan Fu, Bowen Cai, Lin Gao +7
We introduce 3D-FRONT (3D Furnished Rooms with layOuts and semaNTics), a new, large-scale, and comprehensive repository of synthetic indoor scenes highlighted by professionally des…
Hard Example Generation by Texture Synthesis for Cross-domain Shape Similarity Learning
Huan Fu, Shunming Li, Rongfei Jia +3
Image-based 3D shape retrieval (IBSR) aims to find the corresponding 3D shape of a given 2D image from a large 3D shape database. The common routine is to map 2D images and 3D shap…
3D-FUTURE: 3D Furniture shape with TextURE
Huan Fu, Rongfei Jia, Lin Gao +4
The 3D CAD shapes in current 3D benchmarks are mostly collected from online model repositories. Thus, they typically have insufficient geometric details and less informative textur…