In recent times the generation of 3D assets from text prompts has shown impressive results.
Both 2D and 3D diffusion models can help generate decent 3D objects based on prompts …

Despite recent advances in text-to-3D generative methods there is a notable absence of
reliable evaluation metrics. Existing metrics usually focus on a single criterion each such as …

Recent works on text-to-3d generation show that using only 2D diffusion supervision for 3D
generation tends to produce results with inconsistent appearances (eg faces on the back …

Recent innovations on text-to-3D generation have featured Score Distillation Sampling
(SDS) which enables the zero-shot learning of implicit 3D models (NeRF) by directly …

Image-based 3D reconstruction is a challenging task that involves inferring the 3D shape of
an object or scene from a set of input images. Learning-based methods have gained …

We propose a unified framework aimed at enhancing the diffusion priors for 3D generation
tasks. Despite the critical importance of these tasks, existing methodologies often struggle to …

We present GALA3D, generative 3D GAussians with LAyout-guided control, for effective
compositional text-to-3D generation. We first utilize large language models (LLMs) to …

Text-to-3D artistic font generation aims to assist users for innovative and customized 3D font
design by exploring novel concepts and styles. Despite of the advances in the text-to-3D …

Scalable annotation approaches are crucial for constructing extensive 3D-text datasets,
facilitating a broader range of applications. However, existing methods sometimes lead to …

As humans, we aspire to create media content that is both freely willed and readily
controlled. Thanks to the prominent development of generative techniques, we now can …