Computer Vision

Humanoid robots are finally working in 2026, driven by AI breakthroughs rather than robotics advances. Vision-language-action models have replaced hand-coded rules, enabling robots to learn physical tasks through teleope…

Google's SynthID watermarking technology, designed to label AI-generated content and survive edits, is being adopted by OpenAI, Nvidia, Runway, and others, but experts question whether invisible watermarks can effectivel…

London-based Greyparrot has raised $27 million to expand its AI-powered waste analytics platform, which uses computer vision to track and sort recycling data, arguing that the data generated by waste processing is more v…

Researchers have created a tool that traces fake videos back to the specific AI system that generated them by analyzing unique visual fingerprints left by generative models.

A developer demonstrated that prompt-to-model pipelines for computer vision are becoming feasible on consumer hardware by generating nearly 1,000 synthetic images of wrenches using Flux Klein 9B, annotating them with Met…

Researchers propose DisasterTD, a disaster toponym disambiguation framework that integrates multimodal large language models (MLLMs) with cross-view geolocalization to improve geolocalization accuracy of social media ima…

Singapore-based startup Antomation has developed an AI-powered automated baggage loading system called Cargo Cobra that aims to speed up the job by 20% and eliminate the need for human baggage handlers to work inside air…

Researchers have released OpenPVMapper, a nationwide database of rooftop photovoltaic installations in mainland France containing 1,135,850 installations totaling approximately 15.01 GWp of installed capacity, built by a…

Researchers introduce Diff-ID, a diffusion-based framework that enforces identity consistency in facial image generation while delivering photorealistic quality, using a custom 210K image dataset and integrating ArcFace …

Researchers introduce Mage-VL, an efficient codec-native streaming multimodal foundation model that reduces visual token consumption by over 75% while matching or outperforming flagship encoders. The model achieves up to…

Researchers have developed I-LW-DETR, the first fully integer-only lightweight detection transformer, enabling deployment on NPUs and microcontrollers by executing all operations including transformer nonlinearities in i…

Researchers propose WHTMix, a Walsh-Hadamard token mixer that replaces global self-attention in stereo depth estimation transformers, reducing model compute by a factor of 2.46 and single-image inference latency by a fac…

Researchers introduce PerceptionBench, a benchmark designed to evaluate atomic visual perception in multimodal large language models (MLLMs), finding that no model reaches 60% accuracy across ten atomic perceptual capabi…

A forensic reproducibility audit of a chest-radiograph vision-language model benchmark found that 297 of 300 planned model-prompt calls yielded nonempty reports, but 60 Claude calls labeled A/B were executed with the sam…

Researchers introduce OrganLens, a self-supervised method for organ-specific representation learning from CT scans, producing 11 organ-specific representations from a shared encoder without external segmentation masks. I…

Researchers propose OPERA, a multi-agent ensemble framework that treats expert weight assignment as an offline policy learning problem to address distribution shifts in biomedical image analysis. OPERA coordinates hetero…

Researchers have developed ProcAgent, a fully on-device, agentic, vision-based procedural assistant for real-time adaptive guidance on a single NVIDIA Jetson AGX Orin. The system uses a propose-and-verify architecture co…

Researchers introduce IMPRINT, a zero-shot plug-and-play framework that enriches textual object queries with web-sourced images to improve grounding in queryable semantic maps for Object Goal Navigation (ObjectNav). The …

MorphUNet, a diffusion-based face morphing framework introduced in a new arXiv preprint (2607.25092v1), achieves the best Morphing Attack Potential (MAP) of 0.919 on FEI and 0.886 on FRLL when at least three of six recog…

DDH, a Korean dental AI startup, has developed Pano, an AI tool that analyzes panoramic X-rays and uses color coding to highlight potential dental issues, aiming to bridge the trust gap between patients and dentists. Fou…