Program
| Time | Talk | Speaker | Slides |
|---|---|---|---|
| 1:30 - 1:35 | Opening | Timo Milbich | Slides |
| 1:35 - 2:00 | Introduction to Similarity and Deep Metric Learning (20 min + 5 min QA) |
Björn Ommer | Slides |
| 2:00 - 2:45 | DML I: The Family of Objective Functions in DML (40 min + 5 min QA) |
Timo Milbich | Slides |
| 2:45 - 3:15 | Coffee break | ||
| 3:15 - 4:00 | DML II: Beyond Pairs and Triplets - Contextual classification losses (40 min + 5 min QA) (virtual) |
Ismail Elezi | Slides |
| 4:00 - 4:30 | Best Practices in DML - Dataset, Metrics, Tricks, Reality Check (25 min + 5 min QA) |
Jenny Seidenschwarz | Slides |
| 4:30 - 4:50 | Towards Realistic Evaluation of OOD Generalization in DML (15 min + 5 min QA) |
Timo Milbich | Slides |
| 4:50 - 5:10 | Connections between DML and other fields (15 min + 5 min QA) |
Jenny Seidenschwarz | Slides |
Recording
