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20232026
most citedTripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models

3 citations · 6 across the 9 of their papers we have counts for

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11 papers · 1 filter

cs.CV2026

Mira-Scene: Pixel-Aligned Layouts for Generative 3D Scene Reconstruction

Yang-Tian Sun, Tianjia Liu, Zehuan Huang +7

Single-image 3D object generation can now produce high-fidelity assets, yet accurately placing them into a coherent scene layout remains an open challenge. A central difficulty lie…

cs.CV2026

Nexus: Native Mesh Generation with Diffusion

Hanxiao Wang, Ying-Tian Liu, Yuan-Chen Guo +5

Generating high-quality triangle meshes is essential for film, gaming, and interactive 3D applications. Mainstream methods rely on mesh serialization and autoregressive processes,…

cs.CV2025

LaFiTe: A Generative Latent Field for 3D Native Texturing

Chia-Hao Chen, Zi-Xin Zou, Yan-Pei Cao +6

Generating high-fidelity, seamless textures directly on 3D surfaces, what we term 3D-native texturing, remains a fundamental open challenge, with the potential to overcome long-sta…

cs.CV2025

ShapeGen: Towards High-Quality 3D Shape Synthesis

Yangguang Li, Xianglong He, Zi-Xin Zou +4

Inspired by generative paradigms in image and video, 3D shape generation has made notable progress, enabling the rapid synthesis of high-fidelity 3D assets from a single image. How…

cs.CV2025★ 1 cited

OmniPart: Part-Aware 3D Generation with Semantic Decoupling and Structural Cohesion

Yunhan Yang, Yufan Zhou, Yuan-Chen Guo +7

The creation of 3D assets with explicit, editable part structures is crucial for advancing interactive applications, yet most generative methods produce only monolithic shapes, lim…

cs.CV2025

HoloPart: Generative 3D Part Amodal Segmentation

Yunhan Yang, Yuan-Chen Guo, Yukun Huang +5

3D part amodal segmentation--decomposing a 3D shape into complete, semantically meaningful parts, even when occluded--is a challenging but crucial task for 3D content creation and…