Papers Sketch-Based Image Retrieval
“Sketch-Based Image Retrieval” 태그가 달린 논문 114편 · 필터 해제
SeCo-SBIR: Semantically Consistent Prompt Learning for Zero-Shot Sketch-Based Image Retrieval
Adapting CLIP for zero-shot sketch-based image retrieval (ZS-SBIR) via prompt learning faces a fundamental tension: the model must bridge the sketch-photo domain gap through task-specific adaptation, yet the added flexib…
Sketch-Based Image RetrievalZero-shot GeneralizationUNION: A Lightweight Target Representation for Efficient Zero-Shot Image-Guided Retrieval with Optional Textual Queries
Image-Guided Retrieval with Optional Text (IGROT) is a general retrieval setting where a query consists of an anchor image, with or without accompanying text, aiming to retrieve semantically relevant target images. This …
Sketch-Based Image RetrievalDynamic Multi-level Weighted Alignment Network for Zero-shot Sketch-based Image Retrieval
The problem of zero-shot sketch-based image retrieval (ZS-SBIR) has achieved increasing attention due to its wide applications, e.g. e-commerce. Despite progress made in this field, previous works suffer from using imbal…
Sketch-Based Image RetrievalBack To The Drawing Board: Rethinking Scene-Level Sketch-Based Image Retrieval
The goal of Scene-level Sketch-Based Image Retrieval is to retrieve natural images matching the overall semantics and spatial layout of a free-hand sketch. Unlike prior work focused on architectural augmentations of retr…
Sketch-Based Image RetrievalCross-Modal RetrievalSketch Down the FLOPs: Towards Efficient Networks for Human Sketch
As sketch research has collectively matured over time, its adaptation for at-mass commercialisation emerges on the immediate horizon. Despite an already mature research endeavour for photos, there is no research on the e…
Image RetrievalKnowledge DistillationSketch-Based Image RetrievalEnhancing Product Search Interfaces with Sketch-Guided Diffusion and Language Agents
The rapid progress in diffusion models, transformers, and language agents has unlocked new possibilities, yet their potential in user interfaces and commercial applications remains underexplored. We present Sketch-Search…
Image RetrievalRetrievalSketch-Based Image RetrievalComposite Sketch+Text Queries for Retrieving Objects with Elusive Names and Complex Interactions
Non-native speakers with limited vocabulary often struggle to name specific objects despite being able to visualize them, e.g., people outside Australia searching for numbats. Further, users may want to search for such e…
Contrastive LearningImage RetrievalRetrievalSketch-Based Image RetrievalFreestyle Sketch-in-the-Loop Image Segmentation
In this paper, we expand the domain of sketch research into the field of image segmentation, aiming to establish freehand sketches as a query modality for subjective image segmentation. Our innovative approach introduces…
Image RetrievalImage SegmentationSegmentationSemantic Segmentation+1Elevating All Zero-Shot Sketch-Based Image Retrieval Through Multimodal Prompt Learning
We address the challenges inherent in sketch-based image retrieval (SBIR) across various settings, including zero-shot SBIR, generalized zero-shot SBIR, and fine-grained zero-shot SBIR, by leveraging the vision-language …
AllImage RetrievalPrompt LearningRetrieval+2Freeview Sketching: View-Aware Fine-Grained Sketch-Based Image Retrieval
In this paper, we delve into the intricate dynamics of Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) by addressing a critical yet overlooked aspect -- the choice of viewpoint during sketch creation. Unlike photo sy…
DisentanglementImage RetrievalRetrievalSketch-Based Image RetrievalCross-Modal Attention Alignment Network with Auxiliary Text Description for zero-shot sketch-based image retrieval
In this paper, we study the problem of zero-shot sketch-based image retrieval (ZS-SBIR). The prior methods tackle the problem in a two-modality setting with only category labels or even no textual information involved. H…
cross-modal alignmentImage RetrievalRetrievalSketch-Based Image Retrieval+1ARNet: Self-Supervised FG-SBIR with Unified Sample Feature Alignment and Multi-Scale Token Recycling
Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) aims to minimize the distance between sketches and corresponding images in the embedding space. However, scalability is hindered by the growing complexity of solutions,…
Image RetrievalRetrievalSketch-Based Image RetrievalSketchTriplet: Self-Supervised Scenarized Sketch-Text-Image Triplet Generation
The scarcity of free-hand sketch presents a challenging problem. Despite the emergence of some large-scale sketch datasets, these datasets primarily consist of sketches at the single-object level. There continues to be a…
Image GenerationImage RetrievalSketch-Based Image RetrievalTripletDual-Modal Prompting for Sketch-Based Image Retrieval
Sketch-based image retrieval (SBIR) associates hand-drawn sketches with their corresponding realistic images. In this study, we aim to tackle two major challenges of this task simultaneously: i) zero-shot, dealing with u…
Image RetrievalRetrievalSketch-Based Image RetrievalIt's All About Your Sketch: Democratising Sketch Control in Diffusion Models
This paper unravels the potential of sketches for diffusion models, addressing the deceptive promise of direct sketch control in generative AI. We importantly democratise the process, enabling amateur sketches to generat…
AllImage RetrievalRetrievalSketch-Based Image RetrievalText-to-Image Diffusion Models are Great Sketch-Photo Matchmakers
This paper, for the first time, explores text-to-image diffusion models for Zero-Shot Sketch-based Image Retrieval (ZS-SBIR). We highlight a pivotal discovery: the capacity of text-to-image diffusion models to seamlessly…
Image RetrievalRetrievalSketch-Based Image RetrievalHow to Handle Sketch-Abstraction in Sketch-Based Image Retrieval?
In this paper, we propose a novel abstraction-aware sketch-based image retrieval framework capable of handling sketch abstraction at varied levels. Prior works had mainly focused on tackling sub-factors such as drawing s…
Image RetrievalRetrievalSketch-Based Image RetrievalTripletBridging Generative and Discriminative Models for Unified Visual Perception with Diffusion Priors
The remarkable prowess of diffusion models in image generation has spurred efforts to extend their application beyond generative tasks. However, a persistent challenge exists in lacking a unified approach to apply diffus…
DecoderImage GenerationImage RetrievalOpen Vocabulary Semantic Segmentation+3Modality-Aware Representation Learning for Zero-shot Sketch-based Image Retrieval
Zero-shot learning offers an efficient solution for a machine learning model to treat unseen categories, avoiding exhaustive data collection. Zero-shot Sketch-based Image Retrieval (ZS-SBIR) simulates real-world scenario…
Image RetrievalRepresentation LearningRetrievalSketch-Based Image Retrieval+1Symmetrical Bidirectional Knowledge Alignment for Zero-Shot Sketch-Based Image Retrieval
This paper studies the problem of zero-shot sketch-based image retrieval (ZS-SBIR), which aims to use sketches from unseen categories as queries to match the images of the same category. Due to the large cross-modality d…
Image RetrievalKnowledge DistillationRetrievalSketch-Based Image Retrieval