Free4D: Tuning-free 4D Scene Generation with Spatial-Temporal
  Consistency
Authors: name: Tianqi Liu, name: Zihao Huang, name: Zhaoxi Chen, name: Guangcong Wang, name: Shoukang Hu, name: Liao Shen, name: Huiqiang Sun, name: Zhiguo Cao, name: Wei Li, name: Ziwei Liu

We present Free4D, a novel tuning-free framework for 4D scene generation from
a single image. Existing methods either focus on object-level generation,
making scene-level generation infeasible, or rely on large-scale multi-view
video datasets for expensive training, with limited generalization ability due
to the scarcity of 4D scene data. In contrast, our key insight is to distill
pre-trained foundation models for consistent 4D scene representation, which
offers promising advantages such as efficiency and generalizability. 1) To
achieve this, we first animate the input image using image-to-video diffusion
models followed by 4D geometric structure initialization. 2) To turn this
coarse structure into spatial-temporal consistent multiview videos, we design
an adaptive guidance mechanism with a point-guided denoising strategy for
spatial consistency and a novel latent replacement strategy for temporal
coherence. 3) To lift these generated observations into consistent 4D
representation, we propose a modulation-based refinement to mitigate
inconsistencies while fully leveraging the generated information. The resulting
4D representation enables real-time, controllable rendering, marking a
significant advancement in single-image-based 4D scene generation.