computer vision

125 items

ARTICLEDEV.to AI·5/5/2026

We Built Sign Language AI for a Language With Almost No Dataset. Here's What That Actually Looks Like.

This article details the development of OmniSign, a real-time Lebanese Sign Language (LSL) translator, addressing the challenges of building AI for a language with an almost non-existent dataset. The author emphasizes that the hardest problems encountered were not technical but human. The inspiration came from witnessing communication difficulties between a deaf man and a barista in Beirut.

Dataset Low-Resource Language machine learning Sign Language AI

ARTICLEDEV.to AI·4/27/2026

ICE's $7.5M Face-Scanning Glasses Hit Streets by 2027 — And the Industry's Silence Is Complicity

The content describes ICE's plan to deploy $7.5M face-scanning glasses by 2027, marking a significant shift from static forensic analysis to real-time edge-inference identification using computer vision. This initiative raises concerns about the widespread deployment of biometric wearables and the implications for privacy and surveillance.

biometrics Edge AI privacy security

ARTICLEDEV.to AI·5/8/2026

Facial Recognition's 81% Error Rate Is About to Blow Up in Court — Are Your Notes Ready?

The article highlights the 81% error rate of facial recognition in live deployments and its legal implications for developers. They must now focus on documenting methodologies for courtroom defense, signaling the end of the 'black box' AI era.

biometrics security computer vision Facial recognition

RESEARCHarXiv CS.CL·5/5/2026

DIAGRAMS: A Review Framework for Reasoning-Level Attribution in Diagram QA

DIAGRAMS is a review framework for reasoning-level attribution in Diagram Question Answering (Diagram QA). It decouples interface logic from dataset-specific formats via a meta-schema and adapters, facilitating evidence selection and generation.

attribution Diagram QA machine learning computer vision

RESEARCHarXiv CS.CL·5/1/2026

Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling

This paper introduces the Length Value Model (LenVM), a novel token-level framework for modeling the remaining generation length in autoregressive models. By formulating length modeling as a value estimation problem, LenVM provides an annotation-free, scalable, and effective signal for LLMs and VLMs, improving performance on exact length matching tasks.

deep learning Model Architecture computer vision large language models

RESEARCHarXiv CS.AI·5/9/2026

Intelligent CCTV for Urban Design: AI-Based Analysis of Soft Infrastructure at Intersections

This study introduces an AI-enabled analytics framework using existing CCTV infrastructure to evaluate the impact of soft urban interventions on vehicle speed and safety at intersections. Findings from Minneapolis reveal that these interventions significantly reduced vehicle speeds and pass-through traffic at both unsignalized and signalized intersections.

transportation traffic management urban design computer vision

RESEARCHarXiv CS.CL·4/24/2026

Weighting What Matters: Boosting Sample Efficiency in Medical Report Generation via Token Reweighting

This work introduces a token reweighting loss function to enhance data efficiency in training vision-language models for medical report generation. By prioritizing semantically salient tokens, the method achieves comparable report quality using up to ten times less training data.

Data efficiency machine learning computer vision natural language generation

RESEARCHarXiv CS.LG·7d ago

Hoeffding Concept Bottleneck Models with Applications to Overhead Images

Hoeffding Concept Bottleneck Models (HCBM) are introduced to offer non-linear and sparse aggregations of concept scores, enhancing the explainability and accuracy of deep learning predictions. This method leverages Hoeffding functional decomposition of gradient-boosted trees to overcome the limitations of existing linear CBMs, which suffer from a large number of concepts and potential information leakage.

deep learning machine learning computer vision Explainable AI

RESEARCHDEV.to AI·4/25/2026

PP-LCNet: A Lightweight CPU Convolutional Neural Network

PP-LCNet introduces a lightweight convolutional neural network optimized for efficient performance on CPUs. This architecture focuses on achieving high accuracy while maintaining minimal computational demands, making it suitable for resource-constrained environments.

deep learning lightweight models computer vision Convolutional Neural Networks

RESEARCHarXiv CS.CL·27d ago

ReVision: Scaling Computer-Use Agents via Temporal Visual Redundancy Reduction

ReVision introduces a method to scale computer-use agents by reducing temporal visual redundancy in interaction trajectories. It employs a learned patch selector to remove redundant visual tokens, cutting token usage by approximately 46% and improving efficiency for multimodal language models across benchmarks.

multimodal AI LLMs efficiency computer vision

ARTICLE↑ trendingReddit r/MachineLearning·4/27/2026

CVPR Workshop Decisions [D]

A user asks if it's normal for CVPR workshop decisions to be delayed, as they are about five weeks out and need to get travel approved. They don't want to annoy organizers but require acceptance notifications to finalize travel plans.

Workshops computer vision academic conferences CVPR

DOCDEV.to AI·24d ago

Building a License Plate Recognition Engine in C++ — Part 2: Grayscale Image Preprocessing and Local Contrast Edge Detection

This article, part two of a series, details the image preprocessing stage for building a License Plate Recognition (LPR) engine in C++. It covers integral image generation, local contrast analysis, and edge map extraction to enhance regions likely to contain license plate characters for real-time systems.

LPR Image processing learning computer vision

RESEARCHDEV.to AI·4/25/2026

CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos

CoTracker3 introduces a simpler and more effective method for point tracking in videos. It achieves this by utilizing pseudo-labelling on real video data, leading to improved performance.

point-tracking machine learning computer vision pseudo-labelling

ARTICLEDEV.to AI·4/13/2026

The Cop Who Made 3,000 Deepfakes Exposed a Bigger Problem Than Deepfakes

The article highlights a Pennsylvania trooper's 3,000 deepfakes as a warning about technical debt in biometric law, not just a scandal. It argues that lawmakers' rush to define "synthetic media" blurs the line between discriminative and generative AI, creating risks for developers of legitimate facial comparison tools.

regulation biometrics law enforcement computer vision

RESEARCHDEV.to AI·5/7/2026

Foundational Models Defining a New Era in Vision: A Survey and Outlook

This research paper surveys foundational models that are defining a new era in computer vision, offering a comprehensive analysis and future outlook. It examines the impact and emerging trends of these models in the field.

Survey Foundational Models machine learning computer vision

CASEDEV.to AI·4/20/2026

Beyond the Crop: Automating "Ghost Mannequin" Effects with Depth-Aware Inpainting

The content describes how Rewarx Studio AI automates the "ghost mannequin" effect for apparel e-commerce, overcoming depth and occlusion challenges. Their solution involves a three-step pipeline: Semantic Masking (SAM), Depth Estimation (Depth Anything), and Context-Aware Inpainting (SDXL).

Image processing computer vision Inpainting e-commerce

RESEARCHDEV.to AI·4/28/2026

You Only Watch Once: A Unified CNN Architecture for Real-Time SpatiotemporalAction Localization

The title describes a unified CNN architecture for real-time spatiotemporal action localization. This work focuses on improving efficiency and accuracy in detecting activities within videos.

CNN deep learning computer vision Action Recognition

RESEARCHDEV.to AI·4/19/2026

Camera identification with deep convolutional networks

This research explores the use of deep convolutional networks for the specific task of camera identification. It delves into how these advanced AI models can differentiate between various cameras.

deep learning computer vision AI

ARTICLEDEV.to AI·4/27/2026

gsplat: An Open-Source Library for Gaussian Splatting

gsplat is an open-source library dedicated to implementing the Gaussian Splatting technique. It provides tools and resources for 3D reconstruction and rendering applications.

Open Source 3D reconstruction 3D Graphics computer vision

DOCDEV.to AI·4/28/2026

Building a No-Install AI Upscaler: Leveraging Cloud GPUs for Seamless Image Processing

The GoHard AI Upscaler is a browser-based tool for professional-grade image enhancement, removing the need for high-end local rigs. It achieves zero installation and consistent performance by utilizing Python, optimized AI models, and Google Colab cloud GPUs.

Image processing deep learning cloud computing machine learning