Image Outpainting
22 papers with code • 3 benchmarks • 4 datasets
Predicting the visual context of an image beyond its boundary.
Image credit: NUWA-Infinity: Autoregressive over Autoregressive Generation for Infinite Visual Synthesis
Benchmarks
These leaderboards are used to track progress in Image Outpainting
| Trend | Dataset | Best Model | Paper | Code | Compare |
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MS COCO
MSCOCO
Places365
LHQ
Latest papers
In-N-Out: Towards Good Initialization for Inpainting and Outpainting
Our self-supervision method, In-N-Out, is summarized as a training approach that leverages the knowledge of the opposite task into the target model.
ReGO: Reference-Guided Outpainting for Scenery Image
We aim to tackle the challenging yet practical scenery image outpainting task in this work.
Bridging the Visual Gap: Wide-Range Image Blending
julia0607/Wide-Range-Image-Blending
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CVPR 2021
In this paper we propose a new problem scenario in image processing, wide-range image blending, which aims to smoothly merge two different input photos into a panorama by generating novel image content for the intermediate region between them.
Taming Transformers for High-Resolution Image Synthesis
CompVis/taming-transformers
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CVPR 2021
We demonstrate how combining the effectiveness of the inductive bias of CNNs with the expressivity of transformers enables them to model and thereby synthesize high-resolution images.
SiENet: Siamese Expansion Network for Image Extrapolation
nanjingxiaobawang/SieNet-Image-extrapolation
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In this paper, a novel two-stage siamese adversarial model for image extrapolation, named Siamese Expansion Network (SiENet) is proposed.
Enhanced Residual Networks for Context-based Image Outpainting
Although humans perform well at predicting what exists beyond the boundaries of an image, deep models struggle to understand context and extrapolation through retained information.
Very Long Natural Scenery Image Prediction by Outpainting
z-x-yang/NS-Outpainting
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ICCV 2019
The second challenge is how to maintain high quality in generated results, especially for multi-step generations in which generated regions are spatially far away from the initial input.
Image Outpainting and Harmonization using Generative Adversarial Networks
basilevh/image-outpainting
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This way, the hallucinated details are integrated with the style of the original image, in an attempt to further boost the quality of the result and possibly allow for arbitrary output resolutions to be supported.
Multimodal Image Outpainting With Regularized Normalized Diversification
In this paper, we study the problem of generating a set ofrealistic and diverse backgrounds when given only a smallforeground region.
Wide-Context Semantic Image Extrapolation
shepnerd/outpainting_srn
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CVPR 2019
This paper studies the fundamental problem of extrapolating visual context using deep generative models, i. e., extending image borders with plausible structure and details.
