With the development of Internet technology and the popularity of digital devices, Content-
Based Image Retrieval (CBIR) has been quickly developed and applied in various fields …

Conditioned and composed image retrieval extend CBIR systems by combining a query
image with an additional text that expresses the intent of the user, describing additional …

Deep metric learning aims to learn a function mapping image pixels to embedding feature
vectors that model the similarity between images. Two major applications of metric learning …

The mechanical recycling of solid plastic waste on a small-scale level can be accomplished
with the correct approaches. Thermoplastics are the types of plastic mostly considered for …

Matching clothing images from customers and online shopping stores has rich applications
in E-commerce. Existing algorithms encoded an image as a global feature vector and …

We propose CXL-ANNS, a software-hardware collaborative approach to enable highly
scalable approximate nearest neighbor search (ANNS) services. To this end, we first …

Modeling fashion compatibility is challenging due to its complexity and subjectivity. Existing
work focuses on predicting compatibility between product images (eg an image containing a …

In this paper, we propose a multimodal search engine that combines visual and textual cues
to retrieve items from a multimedia database aesthetically similar to the query. The goal of …

At Pinterest, we utilize image embeddings throughout our search and recommendation
systems to help our users navigate through visual content by powering experiences like …

With the advent of large-scale databases in the last two decades, content based image
retrieval (CBIR) has been widely investigated. Studies show that the performance of the …