Exploring clip for assessing the look and feel of images
Measuring the perception of visual content is a long-standing problem in computer vision.
Many mathematical models have been developed to evaluate the look or quality of an …
Many mathematical models have been developed to evaluate the look or quality of an …
Musiq: Multi-scale image quality transformer
Image quality assessment (IQA) is an important research topic for understanding and
improving visual experience. The current state-of-the-art IQA methods are based on …
improving visual experience. The current state-of-the-art IQA methods are based on …
Vila: Learning image aesthetics from user comments with vision-language pretraining
Assessing the aesthetics of an image is challenging, as it is influenced by multiple factors
including composition, color, style, and high-level semantics. Existing image aesthetic …
including composition, color, style, and high-level semantics. Existing image aesthetic …
Hierarchical layout-aware graph convolutional network for unified aesthetics assessment
Learning computational models of image aesthetics can have a substantial impact on visual
art and graphic design. Although automatic image aesthetics assessment is a challenging …
art and graphic design. Although automatic image aesthetics assessment is a challenging …
[PDF][PDF] Rethinking Image Aesthetics Assessment: Models, Datasets and Benchmarks.
Challenges in image aesthetics assessment (IAA) arise from that images of different themes
correspond to different evaluation criteria, and learning aesthetics directly from images while …
correspond to different evaluation criteria, and learning aesthetics directly from images while …
Towards transparent deep image aesthetics assessment with tag-based content descriptors
Deep learning approaches for Image Aesthetics Assessment (IAA) have shown promising
results in recent years, but the internal mechanisms of these models remain unclear …
results in recent years, but the internal mechanisms of these models remain unclear …
Multi-Modality Multi-Attribute Contrastive Pre-Training for Image Aesthetics Computing
In the Image Aesthetics Computing (IAC) field, most prior methods leveraged the off-the-
shelf backbones pre-trained on the large-scale ImageNet database. While these pre-trained …
shelf backbones pre-trained on the large-scale ImageNet database. While these pre-trained …
Theme-aware visual attribute reasoning for image aesthetics assessment
People usually assess image aesthetics according to visual attributes, eg, interesting
content, good lighting and vivid color, etc. Further, the perception of visual attributes …
content, good lighting and vivid color, etc. Further, the perception of visual attributes …
Adaptive fractional dilated convolution network for image aesthetics assessment
To leverage deep learning for image aesthetics assessment, one critical but unsolved issue
is how to seamlessly incorporate the information of image aspect ratios to learn more robust …
is how to seamlessly incorporate the information of image aspect ratios to learn more robust …
Distilling knowledge from object classification to aesthetics assessment
In this work, we point out that the major dilemma of image aesthetics assessment (IAA)
comes from the abstract nature of aesthetic labels. That is, a vast variety of distinct contents …
comes from the abstract nature of aesthetic labels. That is, a vast variety of distinct contents …