PaperSummary13 : MAEThe paper presents Masked Autoencoders (MAEs) as a simple yet scalable self-supervised learning approach for computer vision. Inspired by…1h ago1h ago
PaperSummary12 : Orthogonal Adaptation for modular customization of diffusion modelsThe paper introduces “Orthogonal Adaptation” a new approach for modular customization of text-to-image diffusion models. Traditional…1d ago1d ago
PaperSummary11 : MP-PolarMaskThe paper proposes MP-PolarMask, an extension of PolarMask using multiple auxiliary polar systems, to better handle complex shapes like…2d ago2d ago
PaperSummary10 : Applying eigencontours to polar mask-based instance segmentationThe paper discusses enhancing instance segmentation, which identifies object boundaries in images using eigencontours. Eigencontours are…3d ago3d ago
PaperSummary09 : PolarMask++The paper proposes PolarMask++, a framework that uses polar representation for efficient single-shot instance segmentation. It…4d ago4d ago
PaperSummary08 : PolarMaskThe paper introduces, PolarMask, an anchor box-free, single shot instance segmentation method. It uses polar coordinates to predict…5d ago5d ago
PaperSummary07 : ControlNetThis paper is introduced as a solution to enhance the control over spatial composition in text-to-image diffusion models like Stable…6d ago6d ago
PaperSummary06 : Textual inversionThe paper introduces Textual Inversion, an approach for learning pseudo-words in the embedding space of text-to-image models to represent…Jan 6Jan 6
PaperSummary05 : DreamBoothThe paper provides a fine-tuning approach for personalizing large scale text-to-image diffusion models. With just 3–5 reference images…Jan 51Jan 51
PaperSummary04 : Fine-tuning diffusion models with limited dataThe paper proposes Adapter-Augmented Attention Fine-tuning (A3FT) method for efficient fine-tuning of diffusion models on small datasets…Jan 4Jan 4
