arXiv Computer Vision
JVLGS: Joint Vision-Language Gas Leak Segmentation
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Edge-Aware and Content-Adaptive Infrared Gas Leak Detection for Industrial Safety Monitoring
arXiv:2512. 23234v3 Announce Type: replace-cross Abstract: Infrared gas leak detection is important for industrial safety and environmental monitoring, but automatic detection remains challenging because gas plumes are often faint, small, semi-transparent, and weakly bounded.
arXiv Computer Vision
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OLiVES: An Outdoor Low-Light Video Benchmark for Enhancement and Segmentation
arXiv:2610.20501v1 Announce Type: new Abstract: Low-light video processing remains an underexplored problem in computer vision, primarily due to the scarcity of high-quality ground-truth data. Existi...
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AI-Powered Flare Combustion Efficiency Estimation
The paper presents a lightweight vision‑language encoder paired with a compact multi‑layer perceptron to estimate flare combustion efficiency from low‑cost thermal video. The trained model is deployed via a user‑friendly GUI that overlays efficiency values on each frame, tracks real‑time trends, visualizes distribution across the video, and exports CSV reports. In a six‑month trial, the system maintained 99% uptime with under 15 minutes of weekly maintenance.
arXiv AI
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Zero-Shot Learning in Industrial Scenarios: New Large-Scale Benchmark, Challenges and Baseline
arXiv:2606. 07965v1 Announce Type: new Abstract: Large Visual Language Models (LVLMs) have achieved remarkable success in vision tasks.
arXiv AI
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PR-MaGIC: Prompt Refinement Via Mask Decoder Gradient Flow For In-Context Segmentation
PR-MaGIC is a training‑free, test‑time framework that refines prompts for in‑context image segmentation by using gradient flow from the mask decoder of the Segment Anything Model (SAM). It integrates seamlessly into existing in‑context segmentation pipelines and employs a simple top‑1 selection strategy to stabilize performance. Extensive evaluations show that PR‑MaGIC consistently improves segmentation quality across multiple benchmarks without requiring additional training or architectural changes.
Hugging Face Trending Papers
Jun 3
Scene-Centric Unsupervised Video Panoptic Segmentation
Video panoptic segmentation (VPS) aims to jointly detect, segment, and track all objects while partitioning the video into semantically consistent regions. We introduce the task setting of unsupervised VPS, omitting any human supervision.