# SiENet: Siamese Expansion Network for Image Extrapolation

arXiv: https://arxiv.org/abs/2007.03851 · HTML: https://mlsanity.com/paper/2007.03851/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jul 2020.

## Built on by (most cited first, 18 of 18)

- [Retinexmamba: Retinex-based Mamba for Low-light Image Enhancement](https://mlsanity.com/paper/2405.03349/) (2024)
- [BIPS: Bi-modal Indoor Panorama Synthesis via Residual Depth-aided Adversarial Learning](https://mlsanity.com/paper/2112.06179/) (2021)
- [Underwater Image Restoration via Polymorphic Large Kernel CNNs](https://mlsanity.com/paper/2412.18459/) (2024)
- [High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformer](https://mlsanity.com/paper/2410.22922/) (2024)
- [Test-Time Intensity Consistency Adaptation for Shadow Detection](https://mlsanity.com/paper/2410.07695/) (2024)
- [Enlighten Anything: When Segment Anything Model Meets Low-Light Image Enhancement](https://mlsanity.com/paper/2306.10286/) (2023)
- [Memory augment is All You Need for image restoration](https://mlsanity.com/paper/2309.01377/) (2023)
- [SemIE: Semantically-aware Image Extrapolation](https://mlsanity.com/paper/2108.13702/) (2021)
- [SAM-helps-Shadow:When Segment Anything Model meet shadow removal](https://mlsanity.com/paper/2306.06113/) (2023)
- [DLEN: Dual Branch of Transformer for Low-Light Image Enhancement in Dual Domains](https://mlsanity.com/paper/2501.12235/) (2025)
- [MAC-Lookup: Multi-Axis Conditional Lookup Model for Underwater Image Enhancement](https://mlsanity.com/paper/2507.02270/) (2025)
- [TextMamba: Scene Text Detector with Mamba](https://mlsanity.com/paper/2512.06657/) (2025)
- [Towards Reliable Image Outpainting: Learning Structure-Aware Multimodal Fusion with Depth Guidance](https://mlsanity.com/paper/2204.05543/) (2022)
- [Adaptive Query Prompting for Multi-Domain Landmark Detection](https://mlsanity.com/paper/2404.01194/) (2024)
- [Multi-Object Grounding via Hierarchical Contrastive Siamese Transformers](https://mlsanity.com/paper/2504.10048/) (2025)
- [SFormer: SNR-guided Transformer for Underwater Image Enhancement from the Frequency Domain](https://mlsanity.com/paper/2508.18664/) (2025)
- [A Comprehensive Analysis of Churn Prediction in Telecommunications Using Machine Learning](https://mlsanity.com/paper/2509.22654/) (2025)
- [Forestpest-YOLO: A High-Performance Detection Framework for Small Forestry Pests](https://mlsanity.com/paper/2510.00547/) (2025)

## Abstract (arXiv)

Different from image inpainting, image outpainting has relative less context in the image center to capture and more content at the image border to predict. Therefore, classical encoder-decoder pipeline of existing methods may not predict the outstretched unknown content perfectly. In this paper, a novel two-stage siamese adversarial model for image extrapolation, named Siamese Expansion Network (SiENet) is proposed. In two stages, a novel border sensitive convolution named adaptive filling convolution is designed for allowing encoder to predict the unknown content, alleviating the burden of decoder. Besides, to introduce prior knowledge to network and reinforce the inferring ability of encoder, siamese adversarial mechanism is designed to enable our network to model the distribution of covered long range feature for that of uncovered image feature. The results on four datasets has demonstrated that our method outperforms existing state-of-the-arts and could produce realistic results.