Foundations
Computer Vision
Object detection, segmentation, YOLO, CLIP, and vision-language models
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Showing 212 reads from curated sources
BAIR Blog
👁️ Computer Vision
📄 Paper
⚡ AI Lesson
10mo ago
Whole-Body Conditioned Egocentric Video Prediction
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OpenAI News
👁️ Computer Vision
⚡ AI Lesson
1y ago
Introducing our latest image generation model in the API
Our latest image generation model is now available in the API via ‘gpt-image-1’—enabling developers and businesses to build professional-grade, customizable vis
OpenAI News
👁️ Computer Vision
⚡ AI Lesson
1y ago
Thinking with images
OpenAI o3 and o4-mini represent a significant breakthrough in visual perception by reasoning with images in their chain of thought.
Replicate Blog
👁️ Computer Vision
⚡ AI Lesson
1y ago
Replicate Intelligence #2
Faster image generation, AI-powered world simulator, insights on AI dataset complexity
Weaviate Blog
👁️ Computer Vision
⚡ AI Lesson
2y ago
Using Weaviate to Find Waldo
Dive into using Weaviate for image recognition to find the "needle in a haystack"!
Hugging Face Blog
👁️ Computer Vision
⚡ AI Lesson
3y ago
A Dive into Text-to-Video Models
Hugging Face Blog
👁️ Computer Vision
⚡ AI Lesson
3y ago
Universal Image Segmentation with Mask2Former and OneFormer
Weaviate Blog
👁️ Computer Vision
⚡ AI Lesson
3y ago
How to build an Image Search Application with Weaviate
Learn how to use build an image search application using the Img2vec-neural module in Weaviate.
Hugging Face Blog
👁️ Computer Vision
⚡ AI Lesson
3y ago
Image Classification with AutoTrain
Replicate Blog
👁️ Computer Vision
⚡ AI Lesson
3y ago
Automating image collection
Using CLIP and LAION5B to collect thousands of captioned images.
Distill.pub
👁️ Computer Vision
📄 Paper
⚡ AI Lesson
5y ago
Weight Banding
Weights in the final layer of common visual models appear as horizontal bands. We investigate how and why.
Distill.pub
👁️ Computer Vision
📄 Paper
⚡ AI Lesson
5y ago
High-Low Frequency Detectors
A family of early-vision neurons reacting to directional transitions from high to low spatial frequency.
Distill.pub
👁️ Computer Vision
📄 Paper
⚡ AI Lesson
6y ago
An Overview of Early Vision in InceptionV1
An overview of all the neurons in the first five layers of InceptionV1, organized into a taxonomy of 'neuron groups.'
Distill.pub
👁️ Computer Vision
📄 Paper
⚡ AI Lesson
6y ago
A Discussion of 'Adversarial Examples Are Not Bugs, They Are Features': Two Examples of Useful, Non-Robust Features
An example project using webpack and svelte-loader and ejs to inline SVGs
Lilian Weng's Blog
👁️ Computer Vision
⚡ AI Lesson
7y ago
Object Detection Part 4: Fast Detection Models
In Part 3 , we have reviewed models in the R-CNN family. All of them are region-based object detection algorithms. They can achieve hig
Lilian Weng's Blog
👁️ Computer Vision
⚡ AI Lesson
8y ago
Object Detection for Dummies Part 3: R-CNN Family
[Updated on 2018-12-20: Remove YOLO here. Part 4 will cover multiple fast object detection algorithms, including YOLO.] [Updated on 2018-12-27: Add bbox regress
Lilian Weng's Blog
👁️ Computer Vision
⚡ AI Lesson
8y ago
Object Detection for Dummies Part 2: CNN, DPM and Overfeat
Part 1 of the “Object Detection for Dummies” series introduced: (1) the concept of image gradient vector and how HOG algorithm summarizes the inform
Distill.pub
👁️ Computer Vision
📄 Paper
⚡ AI Lesson
8y ago
Feature Visualization
How neural networks build up their understanding of images
Lilian Weng's Blog
👁️ Computer Vision
⚡ AI Lesson
8y ago
Object Detection for Dummies Part 1: Gradient Vector, HOG, and SS
I’ve never worked in the field of
OpenAI News
👁️ Computer Vision
⚡ AI Lesson
8y ago
Robust adversarial inputs
We’ve created images that reliably fool neural network classifiers when viewed from varied scales and perspectives. This challenges a claim from last week that
DeepCamp AI