FlowSeek: Optical Flow Made Easier with Depth Foundation Models and Motion Bases
About
We present FlowSeek, a novel framework for optical flow requiring minimal hardware resources for training. FlowSeek marries the latest advances on the design space of optical flow networks with cutting-edge single-image depth foundation models and classical low-dimensional motion parametrization, implementing a compact, yet accurate architecture. FlowSeek is trained on a single consumer-grade GPU, a hardware budget about 8x lower compared to most recent methods, and still achieves superior cross-dataset generalization on Sintel Final and KITTI, with a relative improvement of 10 and 15% over the previous state-of-the-art SEA-RAFT, as well as on Spring and LayeredFlow datasets.
Matteo Poggi, Fabio Tosi• 2025
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Optical Flow Estimation | MPI Sintel Final (train) | Endpoint Error (EPE)2.48 | 215 | |
| Optical Flow Estimation | MPI Sintel Clean (train) | EPE1.16 | 208 | |
| Optical Flow | Sintel Final (train) | EPE1.28 | 112 | |
| Optical Flow | Sintel Clean (train) | EPE0.71 | 104 | |
| Optical Flow | KITTI (train) | Fl-all0.039 | 90 | |
| Optical Flow | FlyingThings3D clean (val) | EPE3.94 | 5 | |
| Optical Flow Estimation | TartanAir | End Point Error (EPE)7.694 | 4 | |
| Optical Flow Estimation | Sintel | EPE10.241 | 4 | |
| Optical Flow Estimation | Spring | EPE2.861 | 4 |
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