Dataset Groups Activity Stream VisDA-2017 VisDA-2017 is a simulation-to-real dataset with two extremely distinct domains: Synthetic renderings of 3D models and Real collected from photo-realistic or real-image datasets. BibTex: @dataset{Xingchao_Peng_and_Ben_Usman_and_Neela_Kaushik_and_Judy_Hoffman_and_Dequan_Wang_and_Kate_Saenko_2024, abstract = {VisDA-2017 is a simulation-to-real dataset with two extremely distinct domains: Synthetic renderings of 3D models and Real collected from photo-realistic or real-image datasets.}, author = {Xingchao Peng and Ben Usman and Neela Kaushik and Judy Hoffman and Dequan Wang and Kate Saenko}, doi = {10.57702/t2lmgfnt}, institution = {No Organization}, keyword = {'2017', 'Domain Adaptation', 'Image Classification', 'Images', 'Multiclass Classification', 'Object Recognition', 'Real', 'Simulation', 'VisDA', 'VisDA-2017', 'domain adaptation', 'image classification', 'synthetic to real'}, month = {dec}, publisher = {TIB}, title = {VisDA-2017}, url = {https://service.tib.eu/ldmservice/dataset/visda-2017}, year = {2024} }
