| Optical flow evaluation results |
Statistics:
Average
SD
R2.5
R5.0
R10.0
A50
A75
A95
Error type: angle end-point interpolation normalized interpolation |
|
R10.0 interpolation error |
avg. |
Army (Hidden texture) im0 GT im1 |
Mequon (Hidden texture) im0 GT im1 |
Urban (Synthetic) im0 GT im1 |
Teddy (Stereo) im0 GT im1 |
Backyard (High-speed camera) im0 GT im1 |
Basketball (High-speed camera) im0 GT im1 |
Dumptruck (High-speed camera) im0 GT im1 |
Evergreen (High-speed camera) im0 GT im1 |
||||||||||||||||
| rank | all | disc | untext | all | disc | untext | all | disc | untext | all | disc | untext | all | disc | untext | all | disc | untext | all | disc | untext | all | disc | untext | |
| Spatially variant [22] | 3.5 | 0.16 1 | 0.55 2 | 0.03 10 | 1.16 1 | 3.71 1 | 0.01 1 | 1.77 5 | 4.44 1 | 0.33 4 | 3.73 7 | 7.39 4 | 0.77 5 | 13.4 6 | 21.9 6 | 1.03 4 | 4.47 2 | 18.5 2 | 0.19 2 | 4.77 9 | 25.4 4 | 0.11 2 | 7.88 1 | 19.9 1 | 0.19 3 |
| JIF-Reg [21] | 4.0 | 0.16 1 | 0.55 2 | 0.01 1 | 1.24 5 | 4.21 7 | 0.01 1 | 1.37 1 | 5.28 8 | 0.12 1 | 3.45 2 | 7.57 6 | 0.81 7 | 13.3 4 | 21.7 4 | 1.10 9 | 4.43 1 | 18.2 1 | 0.23 8 | 4.73 7 | 26.0 7 | 0.10 1 | 8.14 4 | 20.6 4 | 0.19 3 |
| CBF [14] | 5.7 | 0.16 1 | 0.53 1 | 0.02 6 | 1.16 1 | 3.76 2 | 0.03 13 | 3.03 15 | 5.17 7 | 1.08 19 | 3.43 1 | 6.97 1 | 0.73 3 | 13.5 7 | 22.0 7 | 1.09 7 | 4.51 3 | 18.6 3 | 0.20 3 | 4.55 4 | 25.5 5 | 0.14 5 | 8.61 9 | 21.8 11 | 0.19 3 |
| F-TV-L1 [17] | 5.7 | 0.17 7 | 0.62 9 | 0.03 10 | 1.44 12 | 4.83 12 | 0.01 1 | 1.43 2 | 5.11 5 | 0.23 2 | 3.52 3 | 7.15 2 | 0.89 10 | 13.1 2 | 21.5 2 | 1.13 13 | 4.56 5 | 18.8 4 | 0.28 9 | 4.43 3 | 24.3 1 | 0.14 5 | 7.95 2 | 20.1 2 | 0.22 14 |
| Fusion [8] | 6.7 | 0.16 1 | 0.55 2 | 0.03 10 | 1.17 3 | 3.93 3 | 0.03 13 | 1.50 3 | 5.15 6 | 0.45 6 | 3.69 5 | 7.56 5 | 0.68 2 | 13.3 4 | 21.8 5 | 1.04 5 | 4.87 12 | 20.0 13 | 0.39 16 | 4.39 1 | 24.4 2 | 0.12 3 | 8.68 13 | 21.9 14 | 0.22 14 |
| Horn & Schunck [6] | 7.2 | 0.21 13 | 0.74 14 | 0.01 1 | 1.42 11 | 4.46 10 | 0.01 1 | 2.08 7 | 5.61 10 | 0.44 5 | 5.14 16 | 8.87 10 | 0.73 3 | 13.5 7 | 22.0 7 | 1.11 10 | 4.55 4 | 18.8 4 | 0.17 1 | 5.07 14 | 26.2 9 | 0.12 3 | 8.46 6 | 21.0 5 | 0.17 1 |
| TV-L1-improved [19] | 7.3 | 0.17 7 | 0.60 7 | 0.02 6 | 1.24 5 | 4.19 6 | 0.01 1 | 2.13 8 | 4.70 3 | 0.56 10 | 3.67 4 | 7.78 7 | 0.79 6 | 13.5 7 | 22.1 9 | 1.13 13 | 4.80 10 | 19.8 10 | 0.30 11 | 4.82 10 | 26.8 13 | 0.26 15 | 8.10 3 | 20.5 3 | 0.18 2 |
| Learning Flow [13] | 9.4 | 0.18 10 | 0.67 11 | 0.01 1 | 1.22 4 | 4.12 4 | 0.01 1 | 2.63 13 | 6.31 14 | 0.85 15 | 4.80 12 | 8.20 8 | 0.65 1 | 14.0 19 | 22.7 19 | 1.18 16 | 4.65 6 | 19.2 7 | 0.30 11 | 4.89 11 | 26.2 9 | 0.17 9 | 8.55 8 | 21.1 7 | 0.20 9 |
| Brox et al. [7] | 9.5 | 0.16 1 | 0.56 5 | 0.03 10 | 1.26 7 | 4.44 8 | 0.03 13 | 1.56 4 | 4.89 4 | 0.24 3 | 3.71 6 | 7.38 3 | 0.98 12 | 13.5 7 | 22.1 9 | 1.27 19 | 5.12 19 | 21.1 19 | 0.43 18 | 4.91 13 | 26.4 12 | 0.20 11 | 8.33 5 | 21.0 5 | 0.22 14 |
| 2D-CLG [3] | 9.5 | 0.22 16 | 0.82 17 | 0.02 6 | 1.32 9 | 4.45 9 | 0.01 1 | 2.07 6 | 4.65 2 | 0.55 9 | 4.68 9 | 8.70 9 | 1.05 13 | 13.6 11 | 22.2 11 | 1.18 16 | 4.84 11 | 20.0 13 | 0.41 17 | 4.76 8 | 26.1 8 | 0.14 5 | 8.49 7 | 21.1 7 | 0.20 9 |
| GraphCuts [16] | 10.6 | 0.16 1 | 0.58 6 | 0.03 10 | 1.68 17 | 5.54 14 | 0.03 13 | 4.03 20 | 6.09 13 | 0.83 14 | 4.36 8 | 9.21 13 | 0.82 8 | 13.6 11 | 22.3 13 | 1.09 7 | 4.66 7 | 19.3 8 | 0.36 14 | 4.39 1 | 24.4 2 | 0.17 9 | 8.88 18 | 22.5 19 | 0.20 9 |
| Second-order prior [10] | 12.6 | 0.18 10 | 0.64 10 | 0.04 17 | 1.27 8 | 4.12 4 | 0.01 1 | 4.70 21 | 7.17 16 | 1.33 22 | 4.79 11 | 9.09 12 | 1.14 14 | 13.2 3 | 21.6 3 | 1.11 10 | 5.05 18 | 20.6 17 | 0.32 13 | 5.13 17 | 28.0 16 | 0.32 17 | 8.64 11 | 21.9 14 | 0.23 18 |
| Black & Anandan 2 [2] | 12.7 | 0.21 13 | 0.74 14 | 0.03 10 | 1.88 18 | 7.16 18 | 0.01 1 | 3.23 16 | 7.79 18 | 1.05 18 | 6.56 18 | 12.0 17 | 0.96 11 | 13.8 16 | 22.6 17 | 1.13 13 | 4.79 9 | 19.8 10 | 0.21 4 | 4.70 5 | 26.3 11 | 0.16 8 | 8.71 15 | 22.0 16 | 0.20 9 |
| Dynamic MRF [9] | 12.8 | 0.17 7 | 0.60 7 | 0.03 10 | 1.32 9 | 4.71 11 | 0.01 1 | 2.16 9 | 6.31 14 | 0.46 7 | 5.05 15 | 9.35 14 | 1.16 15 | 13.6 11 | 22.2 11 | 1.22 18 | 5.40 21 | 22.2 21 | 0.53 21 | 5.12 16 | 28.0 16 | 0.32 17 | 8.69 14 | 21.3 9 | 0.21 13 |
| SPSA-learn [15] | 12.9 | 0.20 12 | 0.69 13 | 0.01 1 | 1.49 13 | 4.88 13 | 0.01 1 | 2.58 11 | 5.69 11 | 0.85 15 | 4.98 13 | 9.00 11 | 0.88 9 | 13.7 15 | 22.3 13 | 1.05 6 | 5.00 17 | 20.6 17 | 0.28 9 | 5.88 22 | 32.8 22 | 0.81 22 | 9.93 20 | 24.9 20 | 0.19 3 |
| Black & Anandan [1] | 13.8 | 0.21 13 | 0.78 16 | 0.01 1 | 1.97 20 | 7.49 19 | 0.03 13 | 3.33 17 | 8.00 19 | 1.11 20 | 9.43 21 | 17.7 21 | 2.48 21 | 13.6 11 | |||||||||||