BoostDream: Efficient Refining for High-Quality Text-to-3D Generation from Multi-View Diffusion

Understand

Witnessing the evolution of text-to-image diffusion models, significant strides have been made in text-to-3D generation.

• Currently, two primary paradigms dominate the field of text-to-3D: the feed-forward generation solutions, capable of swiftly producing 3D assets but often yielding coarse results, and the Score Distillation Sampling (SDS) based solutions, known for generating high-fidelity 3D assets albeit at a slower pace.
• The synergistic integration of these methods holds substantial promise for advancing 3D generation techniques.
• In this paper, we present BoostDream, a highly efficient plug-and-play 3D refining method designed to transform coarse 3D assets into high-quality.