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Found 6 papers, 2 papers with code
Radial Networks: Dynamic Layer Routing for High-Performance Large Language Models
In this work, we explore the practicality of layer sparsity by profiling residual connections and establish the relationship between model depth and layer sparsity.
Exploring the Limits of Semantic Image Compression at Micro-bits per Pixel
Traditional methods, such as JPEG, perform image compression by operating on structural information, such as pixel values or frequency content.
The Right Losses for the Right Gains: Improving the Semantic Consistency of Deep Text-to-Image Generation with Distribution-Sensitive Losses
We test this approach on two baseline models: SSAGAN and AttnGAN (with style blocks to enhance the fine-grained details of the images.)
ArtELingo: A Million Emotion Annotations of WikiArt with Emphasis on Diversity over Language and Culture
This paper introduces ArtELingo, a new benchmark and dataset, designed to encourage work on diversity across languages and cultures.
ZeroWaste Dataset: Towards Deformable Object Segmentation in Cluttered Scenes
Recyclable waste detection poses a unique computer vision challenge as it requires detection of highly deformable and often translucent objects in cluttered scenes without the kind of context information usually present in human-centric datasets.
Journey Towards Tiny Perceptual Super-Resolution
Recent works in single-image perceptual super-resolution (SR) have demonstrated unprecedented performance in generating realistic textures by means of deep convolutional networks.
