Conclusion

Table of Links

Abstract and 1. Introduction

2. Few-Shot Personalized Instance Recognition

3. Object-Conditioned Bag of Instances

4. Experimental Results

5. Conclusion

6. References

5. CONCLUSION

In this paper, we introduced few-shot instance-level personalization of object detectors. We proposed a new method (OBoI) to personalize detection models to recognize user specific instances of object categories. OBoI is a backpropagationfree metric learning approach on a multi-order statistics feature space. We believe that this setup and our method could pave the way to personal instance-level detection and could stimulate future research and applications.