Optical Character Recognition (OCR) is the process of turning images that contain text—such as scanned pages, receipts, or photographs—into machine-readable […]
Category: Computer Vision
Apple Released FastVLM: A Novel Hybrid Vision Encoder which is 85x Faster and 3.4x Smaller than Comparable Sized Vision Language Models (VLMs)
Table of contents Introduction Existing VLM Architectures Apple’s FastVLM Benchmark Comparisons Conclusion Introduction Vision Language Models (VLMs) allow both text […]
Qwen Team Introduces Qwen-Image-Edit: The Image Editing Version of Qwen-Image with Advanced Capabilities for Semantic and Appearance Editing
In the domain of multimodal AI, instruction-based image editing models are transforming how users interact with visual content. Just released […]
Meta AI Just Released DINOv3: A State-of-the-Art Computer Vision Model Trained with Self-Supervised Learning, Generating High-Resolution Image Features
Meta AI has just released DINOv3, a breakthrough self-supervised computer vision model that sets new standards for versatility and accuracy […]
VL-Cogito: Advancing Multimodal Reasoning with Progressive Curriculum Reinforcement Learning
Multimodal reasoning, where models integrate and interpret information from multiple sources such as text, images, and diagrams, is a frontier […]
Meta CLIP 2: The First Contrastive Language-Image Pre-training (CLIP) Trained with Worldwide Image-Text Pairs from Scratch
Contrastive Language-Image Pre-training (CLIP) has become important for modern vision and multimodal models, enabling applications such as zero-shot image classification […]
NASA Releases Galileo: The Open-Source Multimodal Model Advancing Earth Observation and Remote Sensing
Introduction Galileo is an open-source, highly multimodal foundation model developed to process, analyze, and understand diverse Earth observation (EO) data […]
NVIDIA AI Presents ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning
Estimated reading time: 5 minutes Table of contents Introduction The ThinkAct Framework Experimental Results Ablation Studies and Model Analysis Implementation […]
Apple Researchers Introduce FastVLM: Achieving State-of-the-Art Resolution-Latency-Accuracy Trade-off in Vision Language Models
Vision Language Models (VLMs) allow both text inputs and visual understanding. However, image resolution is crucial for VLM performance for […]
VLM2Vec-V2: A Unified Computer Vision Framework for Multimodal Embedding Learning Across Images, Videos, and Visual Documents
Embedding models act as bridges between different data modalities by encoding diverse multimodal information into a shared dense representation space. […]