computer-vision-5

Image Retargeting

3260 papers • 126 benchmarks • 313 datasets

This task has no description! Would you like to contribute one?

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in image-retargeting-5

Trend

Dataset

Best Model

Actions

No benchmarks available.

Libraries

i

Use these libraries to find image-retargeting-5 models and implementations

Datasets

No datasets available.

Subtasks

No subtasks available.

Most implemented papers

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

Yu-Wing Tai, In-So Kweon, Tae-Hyun Oh, Jinsun Park•Tue Aug 08 2017

This paper proposes a weakly- and self-supervised deep convolutional neural network (WSSDCNN) for contentaware image retargeting, which takes a source image and a target aspect ratio, and then directly outpues a retargeted image.

83

Content

0

Paper Graph

Cycle-IR: Deep Cyclic Image Retargeting

Weimin Tan, Bo Yan, Chuming Lin, Xuejing Niu•Wed May 08 2019

This paper proposes a novel deep cyclic image retargeting approach, called Cycle-IR, to firstly implement image Retargeting with a single deep model, without relying on any explicit user annotations, built on the reverse mapping from the retargeted images to the given images.

50 0

Paper Graph

Self-Play Reinforcement Learning for Fast Image Retargeting

T. Yamasaki, Nobukatsu Kajiura, Satoshi Kosugi, Xueting Wang•Wed Feb 26 2020

This study proposes a method of predicting the optimal operator for each step using a reinforcement learning agent, and proposes a reward based on self-play, which will be insensitive to the large variance in the content-dependent distance measured in MULTIOP.

23 0

Paper Graph

OAIR: Object-Aware Image Retargeting Using PSO and Aesthetic Quality Assessment

M. Givkashi, Mohammadreza Naderi, N. Karimi, S. Shirani, S. Samavi•Sat Sep 10 2022

The proposed approach uses image quality assessment and aesthetic quality assessment measures to show superior results compared to popular image retargeting techniques.

1 0

Paper Graph

Supervised deep learning for content-aware image retargeting with Fourier Convolutions

M. Givkashi, Mohammadreza Naderi, N. Karimi, S. Shirani, S. Samavi•Sun Jun 11 2023

A new supervised approach for training deep learning models that uses the original images as ground truth and creates inputs for the model by resizing and cropping the original images to show the desired size and location of the object.

6 0

Paper Graph

Prune and Repaint: Content-Aware Image Retargeting for any Ratio

Feihong Shen, Chao Li, Yifeng Geng, Yongjian Deng, Hao Chen•Tue Oct 29 2024

By focusing on the content and structure of the foreground, the PruneRepaint approach adaptively avoids key content loss and deformation, while effectively mitigating artifacts with local repainting.

3 0

Paper Graph

Adding a benchmark result helps the community track progress.