May 4, 2023 · For BCT, improving the compatibility of two models with less negative impact on retrieval performance is the key challenge. In this paper, we ...

Backward-compatible learning aims to ensure the compatibility of embedding representations between models. As shown in Fig. 1b, the new model can directly.

3. Boundary-aware compatible module is used to obtain a suitable boundary to constrain distance relationship between the new and old embeddings 4.

May 4, 2023 · We first employ adversarial learning to minimize the distribution disparity between embeddings of the new model and the old model. Meanwhile, we ...

Boundary-aware Backward-Compatible Representation via Adversarial Learning in Image Retrieval. Image retrieval plays an important role in the Internet world. ...

May 4, 2023 · In this paper, we proposed a novel backward-compatible training method in image retrieval. To better ensure com- patibility, we designed the ...

Boundary-aware Backward-Compatible Representation via Adversarial Learning in Image Retrieval · 1 code implementation • CVPR 2023.

Dec 16, 2023 · Image retrieval using multiple features often uses explicit weights that represent the importance of the features in their similarity metrics.

We introduce AdvBCT, an Adversarial Backward-Compatible Training method with an elastic boundary constraint that takes both compatibility and discrimination ...

Duration: 6:04
Posted: May 30, 2023