# Weakly- and Self-Supervised Learning for Content-Aware Deep Image Retargeting

arXiv: https://arxiv.org/abs/1708.02731 · HTML: https://mlsanity.com/paper/1708.02731/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Aug 2017.

## Built on by (most cited first, 15 of 15)

- [MAT: Mask-Aware Transformer for Large Hole Image Inpainting](https://mlsanity.com/paper/2203.15270/) (2022)
- [High-Fidelity Pluralistic Image Completion with Transformers](https://mlsanity.com/paper/2103.14031/) (2021)
- [AutoPoster: A Highly Automatic and Content-aware Design System for Advertising Poster Generation](https://mlsanity.com/paper/2308.01095/) (2023)
- [Instance-Level Relative Saliency Ranking with Graph Reasoning](https://mlsanity.com/paper/2107.03824/) (2021)
- [Image Inpainting via Iteratively Decoupled Probabilistic Modeling](https://mlsanity.com/paper/2212.02963/) (2022)
- [Fast Hybrid Image Retargeting](https://mlsanity.com/paper/2203.13595/) (2022)
- [Prune and Repaint: Content-Aware Image Retargeting for any Ratio](https://mlsanity.com/paper/2410.22865/) (2024)
- [OAIR: Object-Aware Image Retargeting Using PSO and Aesthetic Quality Assessment](https://mlsanity.com/paper/2209.04804/) (2022)
- [Retargeting video with an end-to-end framework](https://mlsanity.com/paper/2311.04458/) (2023)
- [Predicting Perceived Gloss: Do Weak Labels Suffice?](https://mlsanity.com/paper/2403.17672/) (2024)
- [HALO: Human-Aligned End-to-end Image Retargeting with Layered Transformations](https://mlsanity.com/paper/2504.03026/) (2025)
- [Object-IR: Leveraging Object Consistency and Mesh Deformation for Self-Supervised Image Retargeting](https://mlsanity.com/paper/2510.27236/) (2025)
- [Screentone-Preserved Manga Retargeting](https://mlsanity.com/paper/2203.03396/) (2022)
- [Supervised Deep Learning for Content-Aware Image Retargeting with Fourier Convolutions](https://mlsanity.com/paper/2306.07383/) (2023)
- [AttenIR: Aligning Dense Visual Attention with Mesh Warping for Unsupervised Image Retargeting](https://mlsanity.com/paper/2610.17743/) (2026)

## Abstract (arXiv)

This paper proposes a weakly- and self-supervised deep convolutional neural network (WSSDCNN) for content-aware image retargeting. Our network takes a source image and a target aspect ratio, and then directly outputs a retargeted image. Retargeting is performed through a shift map, which is a pixel-wise mapping from the source to the target grid. Our method implicitly learns an attention map, which leads to a content-aware shift map for image retargeting. As a result, discriminative parts in an image are preserved, while background regions are adjusted seamlessly. In the training phase, pairs of an image and its image-level annotation are used to compute content and structure losses. We demonstrate the effectiveness of our proposed method for a retargeting application with insightful analyses.