Deep Photo Cropper and Enhancer

学习调色，无需共享照片：面向个性化图像增强的联邦美学偏好学习

Learning Color Grading, No Photo Sharing: Federated Aesthetic Preference Learning for Personalized Image Enhancement

FedPAIE框架通过联邦学习在不集中用户私人照片的情况下，实现了个性化图像增强，平衡了用户偏好与图像保真度，效果良好。

Quantitative Analysis of Automatic Image Cropping Algorithms: A Dataset and Comparative Study

Automatic photo cropping is an important tool for improving visual quality of digital photos without resorting to tedious manual selection. Traditionally, photo cropping is accomplished by determining the best proposal window through visual quality assessment or saliency detection. In essence, the performance of an image cropper highly depends on the ability to correctly rank a number of visually similar proposal windows. Despite the ranking nature of automatic photo cropping, little attention has been paid to learning-to-rank algorithms in tackling such a problem. In this work, we conduct an …

Shallow camera pipeline for night photography rendering

We introduce a camera pipeline for rendering visually pleasing photographs in low light conditions, as part of the NTIRE2022 Night Photography Rendering challenge. Given the nature of the task, where the objective is verbally defined by an expert photographer instead of relying on explicit ground truth images, we design an handcrafted solution, characterized by a shallow structure and by a low parameter count. Our pipeline exploits a local light enhancer as a form of high dynamic range correction, followed by a global adjustment of the image histogram to prevent washed-out results. We proporti…

WESPE: Weakly Supervised Photo Enhancer for Digital Cameras

Low-end and compact mobile cameras demonstrate limited photo quality mainly due to space, hardware and budget constraints. In this work, we propose a deep learning solution that translates photos taken by cameras with limited capabilities into DSLR-quality photos automatically. We tackle this problem by introducing a weakly supervised photo enhancer (WESPE) - a novel image-to-image Generative Adversarial Network-based architecture. The proposed model is trained by under weak supervision: unlike previous works, there is no need for strong supervision in the form of a large annotated dataset of …

4D LUT: Learnable Context-Aware 4D Lookup Table for Image Enhancement

Image enhancement aims at improving the aesthetic visual quality of photos by retouching the color and tone, and is an essential technology for professional digital photography. Recent years deep learning-based image enhancement algorithms have achieved promising performance and attracted increasing popularity. However, typical efforts attempt to construct a uniform enhancer for all pixels' color transformation. It ignores the pixel differences between different content (e.g., sky, ocean, etc.) that are significant for photographs, causing unsatisfactory results. In this paper, we propose a no…

RoGUENeRF：一种面向NeRF的鲁棒几何一致通用增强器

RoGUENeRF: A Robust Geometry-Consistent Universal Enhancer for NeRF

提出RoGUENeRF神经渲染增强器，结合2D预训练与3D几何感知融合，在保持几何一致性和对相机标定鲁棒的同时恢复高频细节，显著提升多种NeRF基线的渲染质量。