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Computer Vision – ECCV 2022

Overview of attention for book
Computer Vision – ECCV 2022
Springer Nature Switzerland

Table of Contents

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    Book Overview
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    Chapter 1 WaveGAN: Frequency-Aware GAN for High-Fidelity Few-Shot Image Generation
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    Chapter 2 End-to-End Visual Editing with a Generatively Pre-trained Artist
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    Chapter 3 High-Fidelity GAN Inversion with Padding Space
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    Chapter 4 Designing One Unified Framework for High-Fidelity Face Reenactment and Swapping
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    Chapter 5 Sobolev Training for Implicit Neural Representations with Approximated Image Derivatives
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    Chapter 6 Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors
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    Chapter 7 3D-FM GAN: Towards 3D-Controllable Face Manipulation
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    Chapter 8 Multi-Curve Translator for High-Resolution Photorealistic Image Translation
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    Chapter 9 Deep Bayesian Video Frame Interpolation
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    Chapter 10 Cross Attention Based Style Distribution for Controllable Person Image Synthesis
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    Chapter 11 KeypointNeRF: Generalizing Image-Based Volumetric Avatars Using Relative Spatial Encoding of Keypoints
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    Chapter 12 ViewFormer: NeRF-Free Neural Rendering from Few Images Using Transformers
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    Chapter 13 L-Tracing: Fast Light Visibility Estimation on Neural Surfaces by Sphere Tracing
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    Chapter 14 A Perceptual Quality Metric for Video Frame Interpolation
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    Chapter 15 Adaptive Feature Interpolation for Low-Shot Image Generation
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    Chapter 16 PalGAN: Image Colorization with Palette Generative Adversarial Networks
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    Chapter 17 Fast-Vid2Vid: Spatial-Temporal Compression for Video-to-Video Synthesis
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    Chapter 18 Learning Prior Feature and Attention Enhanced Image Inpainting
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    Chapter 19 Temporal-MPI: Enabling Multi-plane Images for Dynamic Scene Modelling via Temporal Basis Learning
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    Chapter 21 Temporally Consistent Semantic Video Editing
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    Chapter 22 Error Compensation Framework for Flow-Guided Video Inpainting
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    Chapter 23 Scraping Textures from Natural Images for Synthesis and Editing
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    Chapter 24 Single Stage Virtual Try-On Via Deformable Attention Flows
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    Chapter 25 Improving GANs for Long-Tailed Data Through Group Spectral Regularization
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    Chapter 26 Hierarchical Semantic Regularization of Latent Spaces in StyleGANs
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    Chapter 27 IntereStyle: Encoding an Interest Region for Robust StyleGAN Inversion
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    Chapter 28 StyleLight: HDR Panorama Generation for Lighting Estimation and Editing
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    Chapter 29 Contrastive Monotonic Pixel-Level Modulation
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    Chapter 30 Learning Cross-Video Neural Representations for High-Quality Frame Interpolation
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    Chapter 32 End-to-End Graph-Constrained Vectorized Floorplan Generation with Panoptic Refinement
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    Chapter 33 Few-Shot Image Generation with Mixup-Based Distance Learning
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    Chapter 34 A Style-Based GAN Encoder for High Fidelity Reconstruction of Images and Videos
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    Chapter 35 FakeCLR: Exploring Contrastive Learning for Solving Latent Discontinuity in Data-Efficient GANs
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    Chapter 36 BlobGAN: Spatially Disentangled Scene Representations
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    Chapter 37 Unified Implicit Neural Stylization
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    Chapter 38 GAN with Multivariate Disentangling for Controllable Hair Editing
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    Chapter 39 Discovering Transferable Forensic Features for CNN-Generated Images Detection
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    Chapter 40 Harmonizer: Learning to Perform White-Box Image and Video Harmonization
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    Chapter 41 Text2LIVE: Text-Driven Layered Image and Video Editing
Attention for Chapter 27: IntereStyle: Encoding an Interest Region for Robust StyleGAN Inversion
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Chapter title
IntereStyle: Encoding an Interest Region for Robust StyleGAN Inversion
Chapter number 27
Book title
Computer Vision – ECCV 2022
Published by
Springer, Cham, January 2022
DOI 10.1007/978-3-031-19784-0_27
Book ISBNs
978-3-03-119783-3, 978-3-03-119784-0
Authors

Moon, Seung-Jun, Park, Gyeong-Moon

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 28%
Student > Master 2 11%
Other 1 6%
Researcher 1 6%
Unknown 9 50%
Readers by discipline Count As %
Computer Science 8 44%
Unknown 10 56%