SketchyCOCO: Image Generation From Freehand Scene Sketches
Chengying Gao, Qi Liu, Qi Xu, Limin Wang, Jianzhuang Liu, Changqing Zou
摘要
We introduce the first method for automatic image generation from scene-level freehand sketches. Our model allows for controllable image generation by specifying the synthesis goal via freehand sketches. The key contribution is an attribute vector bridged Generative Adversarial Network called EdgeGAN, which supports high visual-quality object-level image content generation without using freehand sketches as training data. We have built a largescale composite dataset called SketchyCOCO to support and evaluate the solution. We validate our approach on the tasks of both object-level and scene-level image generation on SketchyCOCO. Through quantitative, qualitative results, human evaluation and ablation studies, we demonstrate the method's capacity to generate realistic complex scene-level images from various freehand sketches.
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引用它的顶会 Paper17
- CLIPasso: semantically-aware object sketchingYael Vinker, Ehsan Pajouheshgar, Jessica Y. Bo, Roman Christian Bachmann 等SIGGRAPH 2022 · 被引用 219 次
- Instance-Conditioned GANArantxa Casanova, Marlène Careil, Jakob Verbeek, Michal Drozdzal 等NeurIPS 2021 · 被引用 167 次
- Semi-supervised reference-based sketch extraction using a contrastive learning frameworkChang Wook Seo, Amirsaman Ashtari, Junyong NohSIGGRAPH 2023 · 被引用 14 次
- SwiftSketch: A Diffusion Model for Image-to-Vector Sketch GenerationEllie Arar, Yarden Frenkel, Daniel Cohen-Or, Ariel Shamir 等SIGGRAPH 2025 · 被引用 12 次
- Scene-Level Sketch-Based Image Retrieval with Minimal Pairwise SupervisionCe Ge, Jingyu Wang, Qi Qi, Haifeng Sun 等AAAI 2023 · 被引用 6 次
它引用的顶会 Paper2
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