Image Regression

We provide benchmarks of different domain adaptation algorithms on dSprites and MPI3D . Those domain adaptation algorithms includes:

• MDD: Margin Disparity Discrepancy

Note

• Origin means the accuracy reported by the original paper.

• Avg is the accuracy reported by Transfer-Learn.

• Source Only refers to the model trained with data from the source domain.

• Oracle refers to the model trained with data from the target domain.

Note

Labels are all normalized to [0, 1] to eliminate the effects of diverse scale in regression values.

We repeat experiments on DD for three times and report the average error of the final epoch.

dSprites error on ResNet-18

Methods	Avg	C → N	C → S	N → C	N → S	S → C	S → N
Source Only	0.157	0.232	0.271	0.081	0.220	0.038	0.092
DD	0.057	0.047	0.080	0.030	0.095	0.053	0.037

MPI3D error on ResNet-18

Methods	Avg	RL → RC	RL → T	RC → RL	RC → T	T → RL	T → RC
Source Only	0.176	0.232	0.271	0.081	0.220	0.038	0.092
DD	0.030	0.086	0.029	0.057	0.189	0.131	0.087