Text-guided Eyeglasses Manipulation with Spatial Constraints
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Abstract (arXiv)
Virtual try-on of eyeglasses involves placing eyeglasses of different shapes and styles onto a face image without physically trying them on. While existing methods have shown impressive results, the variety of eyeglasses styles is limited and the interactions are not always intuitive or efficient. To address these limitations, we propose a Text-guided Eyeglasses Manipulation method that allows for control of the eyeglasses shape and style based on a binary mask and text, respectively. Specifically, we introduce a mask encoder to extract mask conditions and a modulation module that enables simultaneous injection of text and mask conditions. This design allows for fine-grained control of the eyeglasses' appearance based on both textual descriptions and spatial constraints. Our approach includes a disentangled mapper and a decoupling strategy that preserves irrelevant areas, resulting in better local editing. We employ a two-stage training scheme to handle the different convergence speeds of the various modality conditions, successfully controlling both the shape and style of eyeglasses. Extensive comparison experiments and ablation analyses demonstrate the effectiveness of our approach in achieving diverse eyeglasses styles while preserving irrelevant areas.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 51 of its 75 references that are in the map. First posted on arXiv 25 Apr 2023.
Builds on
51 of 75 references.
References · 51
- 2014Adam: A Method for Stochastic Optimizationcited by 36,960
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
- 2020Denoising Diffusion Implicit Modelscited by 9,655
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
- 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
- 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
- 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
- 2017Progressive Growing of GANs for Improved Quality, Stability, and Variationcited by 2,967
- 2022Prompt-to-Prompt Image Editing with Cross Attention Controlcited by 2,409
- 2022Null-text Inversion for Editing Real Images using Guided Diffusion Modelscited by 1,168
38 more
- 2021StyleCLIP: Text-Driven Manipulation of StyleGAN Imagerycited by 990
- 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 924
- 2019Interpreting the Latent Space of GANs for Semantic Face Editingcited by 691
- 2019Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?cited by 675
- 2021DiffusionCLIP: Text-Guided Diffusion Models for Robust Image Manipulationcited by 640
- 2019MaskGAN: Towards Diverse and Interactive Facial Image Manipulationcited by 624
- 2020GANSpace: Discovering Interpretable GAN Controlscited by 612
- 2021Designing an Encoder for StyleGAN Image Manipulationcited by 542
- 2017How far are we from solving the 2D & 3D Face Alignment problem? (and a dataset of 230,000 3D facial landmarks)cited by 524
- 2020Closed-Form Factorization of Latent Semantics in GANscited by 407
- 2020StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generationcited by 331
- 2020CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognitioncited by 320
- 2019SEAN: Image Synthesis with Semantic Region-Adaptive Normalizationcited by 253
- 2023An Edit Friendly DDPM Noise Space: Inversion and Manipulationscited by 243
- 2017AttGAN: Facial Attribute Editing by Only Changing What You Wantcited by 241
- 2021General Facial Representation Learning in a Visual-Linguistic Mannercited by 193
- 2020Fast Bi-layer Neural Synthesis of One-Shot Realistic Head Avatarscited by 116
- 2022VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relationscited by 113
- 2021Paint by Wordcited by 107
- 2021HairCLIP: Design Your Hair by Text and Reference Imagecited by 79
- 2021FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizationcited by 71
- 2021Image-to-image Translation via Hierarchical Style Disentanglementcited by 63
- 2022Sparse Local Patch Transformer for Robust Face Alignment and Landmarks Inherent Relation Learningcited by 47
- 2021Image Synthesis via Semantic Compositioncited by 45
- 2021Predict, Prevent, and Evaluate: Disentangled Text-Driven Image Manipulation Empowered by Pre-Trained Vision-Language Modelcited by 34
- 2022AnyFace: Free-style Text-to-Face Synthesis and Manipulationcited by 33
- 2023DeltaEdit: Exploring Text-free Training for Text-Driven Image Manipulationcited by 27
- 2022No Token Left Behind: Explainability-Aided Image Classification and Generationcited by 25
- 2022Towards Counterfactual Image Manipulation via CLIPcited by 19
- 2022FEAT: Face Editing with Attentioncited by 16
- 2021AGRNet: Adaptive Graph Representation Learning and Reasoning for Face Parsingcited by 15
- 2022Bridging CLIP and StyleGAN through Latent Alignment for Image Editingcited by 12
- 2019Unsupervised Eyeglasses Removal in the Wildcited by 10
- 2020ByeGlassesGAN: Identity Preserving Eyeglasses Removal for Face Imagescited by 10
- 2021ISF-GAN: An Implicit Style Function for High-Resolution Image-to-Image Translationcited by 9
- 2022ManiCLIP: Multi-Attribute Face Manipulation from Textcited by 8
- 2020Multi-Density Sketch-to-Image Translation Networkcited by 6
- 2022GlassesGAN: Eyewear Personalization using Synthetic Appearance Discovery and Targeted Subspace Modelingcited by 5
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Citing papers per year: 2023: 1; 2024: 4; 2025: 3; 2026: 2.
10 papers.
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- 2025SEED: A Benchmark Dataset for Sequential Facial Attribute Editing with Diffusion Modelscited by 3
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- 2025SEED: A Benchmark Dataset for Sequential Facial Attribute Editing with Diffusion Models31 May 2025
- 2025Erasing Concepts, Steering Generations: A Comprehensive Survey of Concept Suppression26 May 2025
- 2025Diffusion Model-Based Size Variable Virtual Try-On Technology and Evaluation Method1 Apr 2025
- 2024CLIP-SR: Collaborative Linguistic and Image Processing for Super-Resolution16 Dec 2024
- 2024MICAS: Multi-grained In-Context Adaptive Sampling for 3D Point Cloud Processing25 Nov 2024
- 2024Revealing Directions for Text-guided 3D Face Editing7 Oct 2024
- 2024StableIdentity: Inserting Anybody into Anywhere at First Sight29 Jan 2024
- 2023Counterfactual Co-occurring Learning for Bias Mitigation in Weakly-supervised Object Localization24 May 2023