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cs.CV2026

PI-Light: Physics-Inspired Diffusion for Full-Image Relighting

Zhexin Liang, Zhaoxi Chen, Yongwei Chen +3

Full-image relighting remains a challenging problem due to the difficulty of collecting large-scale structured paired data, the difficulty of maintaining physical plausibility, and…

cs.CV2024

High-Fidelity GAN Inversion for Image Attribute Editing

Tengfei Wang, Yong Zhang, Yanbo Fan +2

We present a novel high-fidelity generative adversarial network (GAN) inversion framework that enables attribute editing with image-specific details well-preserved (e.g., backgroun…

cs.CV2024

ThemeStation: Generating Theme-Aware 3D Assets from Few Exemplars

Zhenwei Wang, Tengfei Wang, Gerhard Hancke +2

Real-world applications often require a large gallery of 3D assets that share a consistent theme. While remarkable advances have been made in general 3D content creation from text…

cs.CV2024

3DTopia: Large Text-to-3D Generation Model with Hybrid Diffusion Priors

Fangzhou Hong, Jiaxiang Tang, Ziang Cao +8

We present a two-stage text-to-3D generation system, namely 3DTopia, which generates high-quality general 3D assets within 5 minutes using hybrid diffusion priors. The first stage…

cs.CV2024

ComboVerse: Compositional 3D Assets Creation Using Spatially-Aware Diffusion Guidance

Yongwei Chen, Tengfei Wang, Tong Wu +3

Generating high-quality 3D assets from a given image is highly desirable in various applications such as AR/VR. Recent advances in single-image 3D generation explore feed-forward m…

cs.CV2024

LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation

Jiaxiang Tang, Zhaoxi Chen, Xiaokang Chen +3

3D content creation has achieved significant progress in terms of both quality and speed. Although current feed-forward models can produce 3D objects in seconds, their resolution i…