activity
20242026
most citedGen-SIS: Generative Self-augmentation Improves Self-supervised Learning

2 citations · 4 across the 16 of their papers we have counts for

collaborators
Showing 2024 · cs.CVShow all

5 papers · 2 filters

cs.CV2024★ 2 cited

Gen-SIS: Generative Self-augmentation Improves Self-supervised Learning

Varun Belagali, Srikar Yellapragada, Alexandros Graikos +7

Self-supervised learning (SSL) methods have emerged as strong visual representation learners by training an image encoder to maximize similarity between features of different views…

cs.CV2024★ 1 cited

ZoomLDM: Latent Diffusion Model for multi-scale image generation

Srikar Yellapragada, Alexandros Graikos, Kostas Triaridis +4

Diffusion models have revolutionized image generation, yet several challenges restrict their application to large-image domains, such as digital pathology and satellite imagery. Gi…

cs.CV2024

Fast constrained sampling in pre-trained diffusion models

Alexandros Graikos, Nebojsa Jojic, Dimitris Samaras

Large denoising diffusion models, such as Stable Diffusion, have been trained on billions of image-caption pairs to perform text-conditioned image generation. As a byproduct of thi…

cs.CV2024

-Brush: Controllable Large Image Synthesis with Diffusion Models in Infinite Dimensions

Minh-Quan Le, Alexandros Graikos, Srikar Yellapragada +3

Synthesizing high-resolution images from intricate, domain-specific information remains a significant challenge in generative modeling, particularly for applications in large-image…

cs.CV2024

Diffusion-Refined VQA Annotations for Semi-Supervised Gaze Following

Qiaomu Miao, Alexandros Graikos, Jingwei Zhang +3

Training gaze following models requires a large number of images with gaze target coordinates annotated by human annotators, which is a laborious and inherently ambiguous process.…