WAFT: Warping-Alone Field Transforms for Optical Flow

Abstract

We introduce Warping-Alone Field Transforms (WAFT), a simple and effective method for optical flow. WAFT is similar to RAFT but replaces cost volume with high-resolution warping, achieving better accuracy with lower memory cost. This design challenges the conventional wisdom that constructing cost volumes is necessary for strong performance. WAFT is a simple and flexible meta-architecture with minimal inductive biases and reliance on custom designs. Compared with existing methods, WAFT ranks 1st on Spring, Sintel, and KITTI benchmarks, achieves the best zero-shot generalization on KITTI, while being 1.3-4.1x faster than existing methods that have competitive accuracy (e.g., 1.3x than Flowformer++, 4.1x than CCMR+). Code and model weights are available at https://github.com/princeton-vl/WAFT.

Cite

Text

Wang and Deng. "WAFT: Warping-Alone Field Transforms for Optical Flow." International Conference on Learning Representations, 2026.

Markdown

[Wang and Deng. "WAFT: Warping-Alone Field Transforms for Optical Flow." International Conference on Learning Representations, 2026.](https://mlanthology.org/iclr/2026/wang2026iclr-waft/)

BibTeX

@inproceedings{wang2026iclr-waft,
  title     = {{WAFT: Warping-Alone Field Transforms for Optical Flow}},
  author    = {Wang, Yihan and Deng, Jia},
  booktitle = {International Conference on Learning Representations},
  year      = {2026},
  url       = {https://mlanthology.org/iclr/2026/wang2026iclr-waft/}
}