PIE

Benchmarks

Task Name	Dataset Name	SOTA Result
Image Editing	PIE Bench	PSNR29.89	25
Trajectory Prediction	PIE (test)	MSE (0.5s)8	25
Multi-view Classification	PIE	Accuracy (PIE)97.94	24
Image Reconstruction	PIE (test)	Relative Error1.2	18
Image Reconstruction	PIE (train)	Relative Error0.009	18
Image Editing	PIE	Distance11.65	18
Pedestrian crossing intention prediction	PIE set03 (test)	Accuracy94	16
Energy-Efficient Code Optimization	PIE	CARET Change9.08	14
Multi-view Classification	PIE (test)	Accuracy95	14
Pedestrian Intention Prediction	PIE	Accuracy93	11
Multi-view Classification	PIE	ECE52.5	11
Pedestrian Trajectory Prediction	PIE 1.0s prediction (test)	ADE7.72	10
Trajectory Prediction	PIE	ADE24.82	10
Clustering	PIE	Clustering Purity69	9
Classification	PIE	Optimal Accuracy (PIE)91.27	9
Subspace Clustering	PIE	Clustering Accuracy52.98	9
Classification	PIE (test)	Accuracy93.8	8
Open Set Domain Adaptation	PIE average of tasks	Acc (OS*)66.4	7
Non-rigid image editing	PIE benchmark	Distance6.12	6
Multi-view Classification	PIE in-domain (test)	Accuracy (Test)92.06	6
Human trajectory prediction	PIE (test)	ADE19.5	5
Trajectory Prediction	PIE	MSE @ 0.5s19	5
Image Editing	PIE (test)	LPIPS0.078	5
Pedestrian Trajectory Prediction	PIE	Time (ms)7.32	4
Pedestrian Trajectory Prediction	PIE 1.5s prediction (test)	ADE13.01	4

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