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#imageprocessing

2 posts2 participants0 posts today
Public
hesselschut
Latenzraum Hbf

A slit-scan video at Amsterdam Centraal railway station, frame by frame interpretaties with CLIP and then fed as a prompt to Stable Diffusion, interpolated between frames with ffmpeg, the minimum pixel values of the resulting movie taken to create this image.
This picture: April 2025
Original video: April 2024

#abstract #railwaystation #imageprocessing #computationalart #generativeart #stableduffusion #clip #slitscan #amsterdam #amsterdamcentraalstation
#amsterdamcentraalstation
Public
Hacker News

Self-Supervised Learning from Images with JEPA

arxiv.org/abs/2301.08243

arXiv logo
arXiv.orgSelf-Supervised Learning from Images with a Joint-Embedding Predictive ArchitectureThis paper demonstrates an approach for learning highly semantic image representations without relying on hand-crafted data-augmentations. We introduce the Image-based Joint-Embedding Predictive Architecture (I-JEPA), a non-generative approach for self-supervised learning from images. The idea behind I-JEPA is simple: from a single context block, predict the representations of various target blocks in the same image. A core design choice to guide I-JEPA towards producing semantic representations is the masking strategy; specifically, it is crucial to (a) sample target blocks with sufficiently large scale (semantic), and to (b) use a sufficiently informative (spatially distributed) context block. Empirically, when combined with Vision Transformers, we find I-JEPA to be highly scalable. For instance, we train a ViT-Huge/14 on ImageNet using 16 A100 GPUs in under 72 hours to achieve strong downstream performance across a wide range of tasks, from linear classification to object counting and depth prediction.
#HackerNews#SelfSupervisedLearning#JEPA
Public
Paul Houle

🥑 NutriTransform: Estimating Nutritional Information From Online Food Posts

(... reminds me of a startup I worked on in the pre-funding stage that would estimate the nutritional content of a meal from a cellphone snap)

arxiv.org/abs/2503.04755

arXiv logo
arXiv.orgNutriTransform: Estimating Nutritional Information From Online Food PostsDeriving nutritional information from online food posts is challenging, particularly when users do not explicitly log the macro-nutrients of a shared meal. In this work, we present an efficient and straightforward approach to approximating macro-nutrients based solely on the titles of food posts. Our method combines a public food database from the U.S. Department of Agriculture with advanced text embedding techniques. We evaluate the approach on a labeled food dataset, demonstrating its effectiveness, and apply it to over 500,000 real-world posts from Reddit's popular /r/food subreddit to uncover trends in food-sharing behavior based on the estimated macro-nutrient content. Altogether, this work lays a foundation for researchers and practitioners aiming to estimate caloric and nutritional content using only text data.
#cs#ai#imageprocessing
Public
GNUTUX

🌟 إطلاق الإصدار v3.5.3 من G'MIC! 🎉

يسرنا الإعلان عن إصدار جديد من G'MIC، صندوق أدوات الفلاتر المفضل لديك! 😇

✨ ما الجديد؟

إضافة فلاتر جديدة.

تحسينات في الأداء.

إصلاح الأخطاء.

تطوير فخور: تم تطويره في @GreycLab بواسطة باحثي @CNRS المتحمسين لمعالجة الصور!

▶️ التحميل: gmic.eu/download.html
▶️ سجل التغييرات: discuss.pixls.us/t/on-the-road

gmic.euG'MIC - GREYC's Magic for Image Computing: A Full-Featured Open-Source Framework for Image Processing - DownloadA full-featured open-source framework for processing generic image (2D,3D,3D+t) with multiple interfaces: command-line (cli), gimp plug-in, web service, Qt plug-in, C++ library
#GMIC#ImageProcessing#OpenSource
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