  Image copy detection is of great importance in real-life social media. In
this paper, a bag of tricks and a strong baseline are proposed for image copy
detection. Unsupervised pre-training substitutes the commonly-used supervised
one. Beyond that, we design a descriptor stretching strategy to stabilize the
scores of different queries. Experiments demonstrate that the proposed method
is effective. The proposed baseline ranks third out of 526 participants on the
Facebook AI Image Similarity Challenge: Descriptor Track. The code and trained
models are available at
https://github.com/WangWenhao0716/ISC-Track2-Submission.
