TP-V1.V2.2
Taxonomy Driven Learning of Semantic Hierarchy of Classes
Ranajoy Sadhukhan, Ankita Chatterjee, Jayanta Mukhopadhyay, Amit Patra, Indian Institute of Technology, Kharagpur, India
Session:
Machine Learning for Image & Video Sensing, Modeling, and Representation
Track:
Applications of Machine Learning
Location:
Gather.Town 2
Presentation Time:
Tue, 4 Oct, 21:00 - 22:00 China Standard Time (UTC +8)
Tue, 4 Oct, 15:00 - 16:00 Central European Time (UTC +2)
Tue, 4 Oct, 13:00 - 14:00 UTC
Tue, 4 Oct, 09:00 - 10:00 Eastern Time (UTC -4)
Tue, 4 Oct, 15:00 - 16:00 Central European Time (UTC +2)
Tue, 4 Oct, 13:00 - 14:00 UTC
Tue, 4 Oct, 09:00 - 10:00 Eastern Time (UTC -4)
Session Co-Chairs:
Jean-Christophe Pesquet, CentraleSupélec and Andrea Cavallaro, Queen Mary University of London and Rebecca Willett, University of Chicago
Presentation
Discussion
Resources
No resources available.
Session TP-V1.V2
TP-V1.V2.1: FACE RECOGNITION FOR FISHEYE IMAGES
Yi-Cheng Lo, Chiao-Chun Huang, Yueh-Feng Tsai, I-Chan Lo, An-Yeu (Andy) Wu, Homer H. Chen, National Taiwan University, Taiwan
TP-V1.V2.2: Taxonomy Driven Learning of Semantic Hierarchy of Classes
Ranajoy Sadhukhan, Ankita Chatterjee, Jayanta Mukhopadhyay, Amit Patra, Indian Institute of Technology, Kharagpur, India
TP-V1.V2.3: DISTILLING FACIAL KNOWLEDGE WITH TEACHER-TASKS: SEMANTIC-SEGMENTATION-FEATURES FOR POSE-INVARIANT FACE-RECOGNITION
Ali Hassani, Zaid El Shair, Rafi Ud Duala Refat, Hafiz Malik, University of Michigan - Dearboorn, United States of America
TP-V1.V2.4: EXPLORING THE SOLUTION SPACE OF LINEAR INVERSE PROBLEMS WITH GAN LATENT GEOMETRY
Antonio Montanaro, Diego Valsesia, Enrico Magli, Politecnico di Torino, Italy
TP-V1.V2.5: BOOSTING THE PERFORMANCE OF WEAKLY-SUPERVISED 3D HUMAN POSE ESTIMATORS WITH POSE PRIOR REGULARIZERS
Lawrence Amadi, Gady Agam, Illinois Institute of Technology, United States of America
TP-V1.V2.6: UTILIZING EXCESS RESOURCES IN TRAINING NEURAL NETWORKS
Amit Henig, Raja Giryes, Tel Aviv University, Israel
TP-V1.V2.7: Dual-ERP Representation for Object Detection in 360° images
Miao Cao, Kiyoharu Aizawa, The University of Tokyo, Japan; Satoshi Ikehata, National Institute of Informatics, Japan
TP-V1.V2.8: EXPLANATORY PARADIGMS IN NEURAL NETWORKS
Ghassan AlRegib, Mohit Prabhushankar, Georgia Institute of Technology, United States of America