Submitted by AutoModerator t3_xznpoh in MachineLearning
vpk_vision t1_irqumk7 wrote
Can I use a global threshold for clustering after training a Person-Reid NN with triplet Loss?
Assume that I have "N" classes in my training data, I train a Person-Reid NN using triplet Loss. In the inference stage I compute scores (using euclidean distance) as follows:
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Class A | Class A | Class B | Class B | Class C | Class C | |
---|---|---|---|---|---|---|
Class A | 0 | 0.6 | 0.8 | 0.79 | 0.88 | 0.88 |
Class A | 0.6 | 0 | 0.71 | 0.71 | 0.87 | 0.87 |
Class B | 0.8 | 0.71 | 0 | 0.70 | 0.86 | 0.86 |
Class B | 0.79 | 0.71 | 0.70 | 0 | 0.85 | 0.85 |
Class C | 0.88 | 0.87 | 0.86 | 0.85 | 0 | 0.80 |
Class C | 0.88 | 0.87 | 0.86 | 0.85 | 0.80 | 0 |
​
The above is a hypothetical N*N score matrix that I have constructed.
Row 1 and Row2 (Column1 and Column2): Class A
Row 3 and Row 4 (Column3 and Column4): Class B
Row 5 and Row 6 (Column5 and Column6): Class C
The only constraint that I have used is that the intraclass distances should be smaller than the interclass distances (which is what triplet Loss does). However a single threshold cannot be used in this case. For example a threshold of 0.6 would work for Class A but not for Class C. Is my understanding correct or am I missing something? Thanks a lot in advance.
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