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The field of Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) is undergoing a paradigm shift, transitioning from specialized models designed for individual tasks to more general retrieval models capable of managing various specialized scenarios. Inspired ...

Conversational image search has emerged as a progressive step beyond traditional keyword-based methodologies, which addresses challenges in human-computer interaction during the information retrieval process. This paper introduces a demonstration called ...

In the rapidly evolving landscape of multimedia data, the need for efficient content-based video retrieval has become increasingly vital. To tackle this challenge, we introduce an interactive video retrieval system designed to retrieve data from vast ...

Sketch-based image retrieval (SBIR) is an essential application of sketches. Research on object-level SBIR is relatively mature, but the study of more complex scene-level SBIR is still in its early stages. In order to advance this research, we ...

Sketch-based image retrieval, which aims to use sketches as queries to retrieve images containing the same query instance, receives increasing attention in recent years. Although dramatic progress has been made in sketch retrieval, few efforts are ...

Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) is an innovative cross-modal task that utilizes a sketch to retrieve corresponding images in the zero-shot learning scene. At present, most algorithms treat ZS-SBIR as a typical image classification ...

Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) is an emerging research task that aims to retrieve data of new classes across sketches and images. It is challenging due to the heterogeneous distributions and the inconsistent semantics across seen and ...

Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) is to use free-hand sketches as queries to perform instance-level retrieval in an image gallery. Existing works usually leverage only high-level information and perform matching in a single region. ...

Searching through existing repositories for a specific mobile app screen design is currently either slow or tedious. Such searches are either limited to basic keyword searches (Google Image Search) or require as input a complete query screen image (...

Keyword-based mobile screen search does not account for screen content and fails to operate as a universal tool for all levels of users. Visual searching (e.g., image, sketch) is structured and easy to adopt. Current visual search approaches count on a ...

Zero-shot sketch-based image retrieval is challenging for the modal gap between distributions of sketches and images and the inconsistency of label spaces during training and testing. Previous methods mitigate the modal gap by projecting sketches and ...

This paper proposes a novel approach for Sketch-Based Image Retrieval (SBIR), for which the key is to bridge the gap between sketches and photos in terms of the data representation. Inspired by channel-wise attention explored in recent years, we present ...

For sketch-based image retrieval (SBIR), we propose a generative adversarial network trained on a large number of sketches and their corresponding real images. To imitate human search process, we attempt to match candidate images with theimaginary image ...

We present a sketch-based image retrieval system, designed to answer arbitrary queries that may go beyond searching for predefined object or scene categories. While sketching is fast and intuitive to formulate visual queries, pure sketch-based image ...

Freehand sketches are a simple and powerful tool for communication. They are easily recognized across cultures and suitable for various applications. In this paper, we use deep convolutional neural networks (ConvNets) to address sketch-based image ...

Despite the extensive usage of decorative patterns in art and design, there is a lack of intuitive ways to find a certain type of patterns. In this paper, we present a multi-level sketch-based interface that incorporates low-level geometrical features ...

In the last few years, the query-by-visual-example paradigm gained popularity, specially for content based retrieval systems. As sketches represent a natural way of expressing a synthetic query, recent research efforts focused on developing algorithmic ...

We present the Sketchy database, the first large-scale collection of sketch-photo pairs. We ask crowd workers to sketch particular photographic objects sampled from 125 categories and acquire 75,471 sketches of 12,500 objects. The Sketchy database gives ...

In this work, we introduce the IdeaPanel system, an interactive sketch-based image search engine with millions of images. IdeaPanel enables users to sketch the target image in their minds and also supports tagging to describe their intentions. After a ...

The explosive growth of touch screens has provided a good platform for sketch-based image retrieval. However, most previous works focused on low level descriptors of shapes and sketches. In this paper, we try to step forward and propose to leverage ...