Domain Adaptation in Computer Vision Applications (eBook)

Dr. Gabriela Csurka is a Senior Scientist in the Computer Vision Team at Naver Labs Europe, Meylan, France.

1. A Comprehensive Survey on Domain Adaptation for Visual Applications Gabriela Csurka 2. A Deeper Look at Dataset Bias Tatiana Tommasi, Novi Patricia, Barbara Caputo, and Tinne Tuytelaars Part I: Shallow Domain Adaptation Methods 3. Geodesic Flow Kernel and Landmarks: Kernel Methods for Unsupervised Domain Adaptation Boqing Gong, Kristen Grauman, and Fei Sha 4. Unsupervised Domain Adaptation based on Subspace Alignment Basura Fernando, Rahaf Aljundi, Rémi Emonet, Amaury Harbard, Marc Sebban, and Tinne Tuytelaars 5. Learning Domain Invariant Embeddings by Matching Distributions Mahsa Baktashmotlagh, Mehrtash Harandi, and Mathieu Salzmann 6. Adaptive Transductive Transfer Machines: A Pipeline for Unsupervised Domain Adaptation Nazli Farajidavar, Teofilo de Campos, and Josef Kittler 7. What To Do When the Access to the Source Data is Constrained? Gabriela Csurka, Boris Chidlovskii, and Stéphane Clinchant Part II: Deep Domain Adaptation Methods 8. Correlation Alignment for Unsupervised Domain Adaptation Baochen Sun, Jiashi Feng, and Kate Saenko 9. Simultaneous Deep Transfer Across Domains and Tasks Judy Hoffman, Eric Tzeng, Trevor Darrell, and Kate Saenko 10. Domain-Adversarial Training of Neural Networks Yaroslav Ganin, Evgeniya Ustinova, Hana Ajakan, Pascal Germain, Hugo Larochelle, François Laviolette, Mario Marchand, and Victor Lempitsky Part III: Beyond Image Classification 11. Unsupervised Fisher Vector Adaptation for Re-Identification Usman Tariq, Jose A. Rodriguez-Serrano, and Florent Perronnin 12. Semantic Segmentation of Urban Scenes via Domain Adaptation of SYNTHIA German Ros, Laura Sellart, Gabriel Villalonga, Elias Maidanik, Francisco Molero, Marc Garcia, Adriana Cedeño, Francisco Perez, Didier Ramirez, Eduardo Escobar, Jose Luis Gomez, David Vazquez, and Antonio M. Lopez 13. From Virtual to Real World Visual Perception using Domain Adaptation – The DPM as Example Antonio M. López, Jiaolong Xu, José L. Gómez, David Vázquez, and Germán Ros 14. Generalizing Semantic Part Detectors Across Domains David Novotny, Diane Larlus, and Andrea Vedaldi Part IV: Beyond Domain Adaptation: Unifying Perspectives 15. A Multi-Source Domain Generalization Approach to Visual Attribute Detection Chuang Gan, Tianbao Yang, and Boqing Gong 16. Unifying Multi-Domain Multi-Task Learning: Tensor and Neural Network Perspectives Yongxin Yang and Timothy M. Hospedales