Attention-GAN for Object Transfiguration in Wild Images
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Summary
Experimental results demonstrate the necessity of investigating attention in object transfiguration, and that the proposed algorithm can learn accurate attention to improve quality of generated images.
- Type
- preprint
- Published
- 2018-03-19
- Cited by
- 192
- References
- 42
- Access
- Open access
- OpenAlex
- https://openalex.org/W2793149861
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3969005
Keywords
Object (grammar), Computer science, Artificial intelligence, Domain (mathematical analysis), Segmentation
References
- Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
- Describing Videos by Exploiting Temporal Structure
- Image Super-Resolution Using Deep Convolutional Networks
- Fully convolutional networks for semantic segmentation
- The application of two-level attention models in deep convolutional neural network for fine-grained image classification
- ImageNet: A large-scale hierarchical image database
- Attention to Scale: Scale-Aware Semantic Image Segmentation
- Generating images with recurrent adversarial networks
- Learning Deep Features for Discriminative Localization
- Generating Images Part by Part with Composite Generative Adversarial Networks
- Deep Feature Interpolation for Image Content Changes
- Image-to-Image Translation with Conditional Adversarial Networks
- Learning to Generate Images of Outdoor Scenes from Attributes and Semantic Layouts
- Scribbler: Controlling Deep Image Synthesis with Sketch and Color
- StackGAN: Text to Photo-Realistic Image Synthesis with Stacked Generative Adversarial Networks
- Learning from Simulated and Unsupervised Images through Adversarial Training
- Least Squares Generative Adversarial Networks
- DualGAN: Unsupervised Dual Learning for Image-to-Image Translation
- Perceptual Adversarial Networks for Image-to-Image Transformation
- Tag Disentangled Generative Adversarial Network for Object Image Re-rendering
Cited by
- Perceptual Adversarial Networks for Image-to-Image Transformation
- Unsupervised Attention-guided Image to Image Translation
- Language Guided Fashion Image Manipulation with Feature-wise Transformations
- Collaging on Internal Representations: An Intuitive Approach for Semantic Transfiguration
- Smooth Deep Image Generator from Noises
- Class Activation Map Generation by Representative Class Selection and Multi-Layer Feature Fusion
- Single-Image De-Raining With Feature-Supervised Generative Adversarial Network
- Unsupervised Object-Level Image-to-Image Translation Using Positional Attention Bi-Flow Generative Network
- Unsupervised Semantic-Preserving Adversarial Hashing for Image Search
- Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation
- A Survey of Unsupervised Deep Domain Adaptation
- DistillHash: Unsupervised Deep Hashing by Distilling Data Pairs
- What and Where to Translate: Local Mask-based Image-to-Image Translation
- Mask Based Unsupervised Content Transfer
- Multi-Channel Attention Selection GAN With Cascaded Semantic Guidance for Cross-View Image Translation
- RAG: Facial Attribute Editing by Learning Residual Attributes
- GAN-Based virtual-to-real image translation for urban scene semantic segmentation
- Disentangled Makeup Transfer with Generative Adversarial Network
- Improving the Harmony of the Composite Image by Spatial-Separated Attention Module
- SPA-GAN: Spatial Attention GAN for Image-to-Image Translation
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