LiteFlowNet2-ft
Reported on 5 benchmarks across 1 task · 1 paper · 2 SOTA
Note: results are matched by exact model name. Different papers may use the same name for different model variants.
Computer Vision5 results
- Average End-Point Error· 2019-03-15SOTA1.4best: 0.8 (CroCo-Flow)
- Out-Noc· 2019-03-15SOTA2.63
- Average End-Point Error· 2019-03-153.48best: 0.963 (MEMFOF-L)
- Average End-Point Error· 2019-03-154.69best: 1.907 (MEMFOF-L)
- Fl-all· 2019-03-157.62best: 11.22 (FastFlowNet-ft)