A curated list of 3D Vision papers relating to Robotics domain in the era of large models i.e. LLMs/VLMs, inspired by awesome-computer-vision, including papers, codes, and related websites

A list of popular deep learning models related to classification, segmentation and detection problems

A curated list of awesome datasets with human label variation (un-aggregated labels) in Natural Language Processing and Computer Vision, accompanying The 'Problem' of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation (EMNLP 2022)

CLIP is an open source, multimodal computer vision model and it's awesome!

In this latest updated demo of this really awesome app I created using PowerApps, I showcase how I am able to extract EXIF metadata data properties including the Longitude, Latitude, Altitude, Address, Basic Tags (outdoor / indoor / person), ThumbnailUrl, Camera Make, Model, blah, blah, blah all within a single Power Automate flow containing less than 20 steps in total, 10 of which are simply initializing and setting variables, with paging comes to a whooping 45 seconds on averages per 5000 photos processed from a SharePoint Site Assets Library containing over R10k of photos. About 25% of which are photos between 4MB and 20MB. No Cognitive Services Computer Vision API. No complex code. No 4MB file limit. Genuinely absolutely free 🤩.

A curated list of awesome frameworks, libraries, tools, tutorials, research papers, and resources for deep learning. This list covers neural networks, model optimization, NLP, computer vision, and other deep learning applications.

A curated list of awesome NLP, Computer Vision, Model Compression, XAI, Reinforcement Learning, Security, etc Paper

Deploy awesome computer vision model use tensorrt

Awesome Diffusion Models: a curated list of Generative Diffusion Models in Computer Vision

A curated list for awesome model implement for computer vision

Deep Learning is awesome, it has given wings to computer vision and object detection/classification. We can even read number plates from images and automatically challan them if they are violating traffic rules. There are two ways of Doing number plate OCR. First way is to separate each character and then do OCR character by character. Other way is to feed the whole plate together. We need to see you you do in first approach. For test data, go to olx and download few sample car and bike images to test. You model/algorithm should be robust enough to work for one line and two line number plates, should be able to work on whilte, yellow and green background standard number plates.