Sketch-Based Image Retrieval
36 papers with code • 3 benchmarks • 4 datasets
Benchmarks
These leaderboards are used to track progress in Sketch-Based Image Retrieval
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Chairs
Quick, Draw! Dataset
ShoeV2
QuickDraw-Extended
Latest papers with no code
Dual-Modal Prompting for Sketch-Based Image Retrieval
In this study, we aim to tackle two major challenges of this task simultaneously: i) zero-shot, dealing with unseen categories, and ii) fine-grained, referring to intra-category instance-level retrieval.
Text-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).
How to Handle Sketch-Abstraction in Sketch-Based Image Retrieval?
@q loss to inject that understanding into the system.
Bridging Generative and Discriminative Models for Unified Visual Perception with Diffusion Priors
Our purpose is to establish a unified visual perception framework, capitalizing on the potential synergies between generative and discriminative models.
Modality-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.
Active Learning for Fine-Grained Sketch-Based Image Retrieval
The ability to retrieve a photo by mere free-hand sketching highlights the immense potential of Fine-grained sketch-based image retrieval (FG-SBIR).
A Recipe for Efficient SBIR Models: Combining Relative Triplet Loss with Batch Normalization and Knowledge Distillation
Then, we introduce a Relative Triplet Loss (RTL), an adapted triplet loss to overcome those limitations through loss weighting based on anchors similarity.
Adapt and Align to Improve Zero-Shot Sketch-Based Image Retrieval
Zero-shot sketch-based image retrieval (ZS-SBIR) is challenging due to the cross-domain nature of sketches and photos, as well as the semantic gap between seen and unseen image distributions.
If At First You Don't Succeed: Test Time Re-ranking for Zero-shot, Cross-domain Retrieval
In this paper we propose a novel method for zero-shot, cross-domain image retrieval in which we make two key contributions.
Sketch-an-Anchor: Sub-epoch Fast Model Adaptation for Zero-shot Sketch-based Image Retrieval
Sketch-an-Anchor is a novel method to train state-of-the-art Zero-shot Sketch-based Image Retrieval (ZSSBIR) models in under an epoch.
