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Earlier sources: Computer vision
Computer vision uses computational models to interpret images and video. Follow recognition, detection, segmentation, visual understanding, and evaluation across research and practical systems.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗2 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- arXiv · Published · First archived
Hard Vision, Easy Vision: What GPT-6 Astra Reveals Across Computer Vision ↗
Frontier general-purpose systems are rapidly expanding beyond visual understanding into capabilities traditionally handled by dedicated computer-vision models. As these capabilities expand, a central question for the computer-vision community is how far this reach extends, and what remains hard. We evaluate GPT-6 Astra alongside five frontier general-purpose AI systems across 34 capabilities and 55 benchmarks spanning nine areas of computer vision. We compare their performance with dedicated models and humans where suitable references are available. Astra demonstrates broad visual capability,…
- arXiv · Published · First archived
A Computer Vision Approach to Visual Fraud Detection in Phishing Websites Using YOLOv8 ↗
Phishing remains one of the most common vectors for financial and identity fraud, and most detection systems still rely on inspecting a page's URL, HTML markup, or domain registration history. These signals are easy for an attacker to rotate or obfuscate, and they say very little about what actually convinces a victim to hand over a password or a card number: the way the page looks. This paper describes a visual, image-based approach to phishing detection that treats a rendered webpage the same way a human eye would, as a picture that either matches a trusted brand or doesn't. A YOLOv8 convolu…
- GitHub · Repository created · First archived
zhangyyy-ai-rs/GazeEarth ↗
The Earth in One Gaze: Training-Free Active Focus for UHR Remote Sensing Understanding
- GitHub · Repository created · First archived
OmniJev/OneJev ↗
🚀🚀 A multimodal System One decision model that gives calibrated answers to typed questions about screens, photos, video and text in one forward pass.
- OpenAlex · Published · First archived
Automated pavement marking retroreflectivity estimation via computer vision and machine learning ↗
Pavement marking retroreflectivity is essential for nighttime road safety but deteriorates due to environmental and traffic factors. Traditional assessment methods are costly and labor-intensive. This paper introduces a sensor-independent, artificial intelligence driven methodology for predicting pavement-marking retroreflectivity using just Red, Green, and Blue (RGB) smartphone videos. The artificial intelligence contribution is through combining gray level co-occurrence matrix (GLCM) based texture and contrast features with a physics-informed synthetic labeling model that imitates material d…
- GitHub · Repository created · First archived
Makankn/laya-plays-google-snake ↗
Real Google Snake controlled from pixels and arrow keys, not a clone. Laya chooses moves; vision tracking handles the browser.
- GitHub · Repository created · First archived
tomascupr/reelql ↗
Give your agent eyes: any video link in, one typed JSON out. A Claude skill + API.
- GitHub · Repository created · First archived
aashish254/Aniflow ↗
🎬 Autonomous AI Studio for Manhwa & Webtoon Recaps — Vision Pipeline (YOLOv8 + Magi v2), Multi-Voice TTS & Video Synthesis
- GitHub · Repository created · First archived
yoheinakajima/glance-speedlab ↗
A measurement-first lab for low-latency local camera inference with Glance.
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Computer vision
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
See the collection and counting methodology ↗ · Read the weekly synthesis ↗
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