YOLOvX

?? YOLOE: Open-Set Object Detection & Segmentation without Training YOLO are fast and accurate but limited to predefined categories. Open-set methods address this but often sacrifice efficiency. YOLOE changes this by integrating text, visual, and prompt-free detection into a single, highly efficient model—achieving real-time “see anything” capability, check YOLOvX Demos below.???? ?? Text Prompts – RepRTA refines embeddings with zero inference overhead. ?? Visual Prompts – SAVPE enhances visual embeddings with minimal complexity. ?? Prompt-Free – LRPC detects all objects efficiently, without language model dependencies. ?? Why YOLOE? ? 3× lower training cost & 1.4× faster inference vs. YOLO-Worldv2-S (+3.5 AP on LVIS) ? 4× less training time than YOLOv8-L with superior COCO performance (https://lnkd.in/gv-tTMny) ?? Real-World Use Cases: ?? Industrial Conveyors – Automate real-time object detection & quality control for manufacturing lines. (See below conveyor videos for detecting oranges and caps in motion!) ?? Autonomous Vehicles – Identify unknown objects on the road. ?? Surveillance – Detect threats dynamically. ?? Retail – Adapt checkout systems for any product. ?? Healthcare – Assist in anomaly detection. Awesome work by: ao wang, Lihao Liu, Hui Chen, Zijia Lin, Jungong Han, Guiguang Ding, Piotr Skalski ?? Stay tuned for more exciting developments and breakthroughs on the horizon! ? WISERLI YOLOvX OpenCV Roboflow Ultralytics Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #ComputerVision #YOLOE #ObjectDetection #AI #YOLOvX #MachineLearning

?? Parking Management with YOLO OBB ??? ?? YOLO OBB (You Only Look Once with Oriented Bounding Boxes) for real-time parking detection with remarkable precision. ?? System accurately identifies vehicles using advanced computer vision techniques, tracking parking occupancy and delivering instant updates on available spots. The interface displays live counts directly on video feeds, giving operators immediate visibility into their parking assets. Use Cases: ??? Shopping malls optimizing customer experience by reducing parking search time ?? University campuses managing limited parking resources during peak class hours ?? Corporate offices tracking employee parking utilization to right-size facilities ?? Airports improving passenger flow by directing drivers to nearest available spots What parking challenges could this solve? Awesome work by: Harsha Tejas ?? Stay tuned for more exciting developments and breakthroughs on the horizon! ? WISERLI YOLOvX OpenCV Roboflow Ultralytics Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #ComputerVision #SmartParking #YOLOvX #OBB #AI #Innovation #UrbanMobility

Sports Analytics with Computer Vision ???? An AI-Powered Padel Analytics system that delivers: ? Real-time player tracking with custom Kalman filter + re-ID hybrid tracker ? Full skeleton detection and pose estimation ? Comprehensive metrics: position/velocity data, distance covered, time in strategic zones ? Automatic team attribution ? Players can trigger custom highlights by simply facing the camera and raising both hands! ?? It tracks everything in real-time at 50+ FPS on an NVIDIA RTX 3070 (with games only running at 30FPS, to have processing power to spare). Awesome work by: Jo?o Freitas da Silva ?? Stay tuned for more exciting developments and breakthroughs on the horizon! ? WISERLI YOLOvX OpenCV Roboflow Ultralytics Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #ComputerVision #PadelAnalytics #Sports #AI #YOLOvX #Innovation #MachineLearning #TechInSports

?? Real-time?On-prem Detection Database and Stream from YOLOvX App ?? Real-Time Detection and Analytics with YOLOvX! Here we’re highlighting real-time object detection and advanced analytics that empower smarter decisions. But we’re not stopping there—our system takes it further with a specialized use case. ?? Highlighting Use Case: Finding Empty Spaces Imagine effortlessly identifying vacant areas in real-time—be it parking lots, warehouses, or office spaces. With the YOLOvX App Dashboard, powered by real-time detection and connected analytics, space optimization has never been this seamless. ?? Watch our app in action: ? Smart Detection for Empty Spaces ? Real-Time Insights, Visualized ? Connected Analytics for Smarter Decisions Update/Install your YOLOvX Beta app today on Google Play or the App Store and experience the future of mobile detection. ???? We are working on optimizing YOLOvX for mobile app—focusing on efficiency, accuracy, and seamless integration. Check out at: yolovx.com ?? ? Android: https://lnkd.in/gV-mVp7j ? iOS: https://lnkd.in/gJmXWATe ?? Let us know, and stay tuned for more updates as we continue to push the boundaries of real-time object detection. ? WISERLI YOLOvX Roboflow Ultralytics OpenCV Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #ComputerVision #AI #EdgeComputing #YOLOvX #CustomVisionModel #RealTimeAnalytics #EmptySpaces #Detection #Industry #Innovation

Face Re-identification 2.0: Tracking Guests & Unknowns ?? Traditional face recognition systems only identify registered users, leaving gaps in tracking guests and unknown individuals. This leads to security blind spots, inefficient visitor management, and lost re-identification opportunities. ?? This advanced face reidentification system: ? Identifies registered members ? Assigns unique guest IDs for re-identification while ensuring privacy compliance ? Tracks unknowns for enhanced security Use Cases: ?? Corporate Security – Manage employee & visitor access seamlessly ??? Event Management – Track attendees, VIPs, and unidentified visitors ?? Hotels & Resorts – Recognize repeat guests for personalized service ?? Healthcare – Monitor patient movements & prevent unauthorized entry ?? Supermarkets & Retail – Identify repeat customers for loyalty programs & detect potential shoplifters By using guest IDs instead of personal data, we ensure privacy compliance while maintaining seamless security and visitor tracking. Seamless, smart, and future-ready! What industries or locations would benefit most from this system? ?? Stay tuned for more exciting developments and breakthroughs on the horizon! ? WISERLI YOLOvX OpenCV Roboflow Ultralytics Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #AI #FaceRecognition #ComputerVision #Security #YOLOvX #Innovation

??Real-Time Traffic Management with Computer Vision ??? An innovative project that turns ordinary CCTV cameras into powerful traffic analysis tools! ???? ? Integrated Supervision Polygon Tool with CCTV footage ? Used OpenCV for image processing and analysis ? Implemented lane-by-lane traffic monitoring capabilities Real-Time Insights Delivered: ?? Unauthorized emergency lane usage detection ?? Lane-specific traffic flow analysis (speed and density) ?? Vehicle counting with classification ?? Traffic pattern visualization Potential: ? Higher-resolution cameras could detect more violation types ? Potential for automated license plate recording and enforcement Awesome work by: Baha K?z?l ?? Stay tuned for more exciting developments and breakthroughs on the horizon! ? WISERLI YOLOvX OpenCV Roboflow Ultralytics Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #ComputerVision #TrafficManagement #AI #YOLOvX #Innovation #SmartCities #Roboflow #YOLO

?? Fall Detection in Real-World Conditions ?? An enhanced fall detection model that significantly improves performance in challenging real-world scenarios. ?? This addresses key limitations of conventional systems: ? The model maintains high accuracy across different lighting conditions, from bright daylight to dimly lit indoor spaces ???? ? Algorithm can differentiate between similar actions that typically trigger false alarms, such as distinguishing between intentional kneeling and actual falls ??♂? vs ?? ? The system successfully handles multi-person scenarios, tracking individuals separately without confusion ???? The accompanying video demonstrates these capabilities in action. A significant step forward for elderly care applications, healthcare facilities, and other safety monitoring systems where reliable fall detection can mean the difference between timely intervention and delayed assistance. Awesome work by: parichehr vahidinia ?? Stay tuned for more exciting developments and breakthroughs on the horizon! ? WISERLI YOLOvX OpenCV Roboflow Ultralytics Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #FallDetection #AI #YOLOvX #Innovation #ElderCare #SafetyTech #ComputerVision

?? Distill Any Depth: Monocular Depth Estimation ?? Exciting research on how we understand depth from a single image! The latest work tackles a critical challenge in computer vision: how to accurately estimate scene depth using just one RGB image. Key highlights: ? Outperformed SOTA models like MiDaS v3.1, DepthAnythingv2, Marigold, and Genpercept ? Introduced Cross-Context Distillation, a novel approach that combines global and local depth cues ? Developed a multi-teacher distillation framework leveraging complementary model strengths Watch the video below to see it in action! ???? Awesome work by: Xiankang He, Dongyan Guo,?Hongji Li,?Ruibo Li,?Ying Cui, Zhang Chi at Zhejiang University of Technology, Nanyang Technological University Singapore, Westlake University, Lanzhou University ?? Stay tuned for more exciting developments and breakthroughs on the horizon! ? WISERLI YOLOvX OpenCV Roboflow Ultralytics Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #ComputerVision #AI #YOLOvX #MachineLearning #DeepLearning #Research #Innovation

?? Real-Time Tool Bits Detection with YOLOvX App Dashboard ?? A system that identifies and monitors tool bits in real-time (flathead, torx, hex socket, flathead long, etc.) with remarkable accuracy using our YOLOvX App running a custom tool bits detection model entirely on-device! ??? ?? Check out the demo video below showing our system in action. The magic happens locally on your device - no cloud processing needed - while the YOLOvX App shares data with a real-time monitoring dashboard accessible via web browser in local network ?? to analyze patterns, usage frequency, and record session history. ?? ?? This solution is perfect for: ?? Workshop quality control ?? Assembly line optimization ???? Training new technicians ?? Inventory management Who else sees applications for this technology in their industry? Let's discuss how this approach could transform your workflows. ?? ?? Update/Install your YOLOvX Beta app today on Google Play or the App Store and experience the future of mobile detection. ???? We are working on optimizing YOLOvX for mobile app—focusing on efficiency, accuracy, and seamless integration. Check out at: yolovx.com ?? ? Android: https://lnkd.in/gV-mVp7j ? iOS: https://lnkd.in/gJmXWATe ?? Stay tuned for more exciting developments and breakthroughs on the horizon! ? WISERLI YOLOvX Roboflow Ultralytics OpenCV Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #ComputerVision #AI #EdgeComputing #YOLOvX #CustomVisionModel #RealTimeAnalytics #ToolDetection #Industry #Innovation

?? Advancing Multi-View Object Tracking with MITracker ???? Multi-view object tracking (MVOT) presents significant advantages over single-view tracking, addressing challenges like occlusion and target loss. However, progress has been hindered by the lack of comprehensive datasets To overcome these limitations, researchers have introduced MITracker, a novel MVOT method that efficiently integrates multi-view object features for stable and accurate tracking. Alongside this, they present MVTrack, a large-scale dataset comprising 234K high-quality annotated frames and 27 distinct objects across diverse environments. Key Innovations of MITracker: ? Transforms 2D image features into a 3D spatial representation for cross-view fusion ? Utilizes Bird’s Eye View (BEV) compression to enhance tracking accuracy ? Introduces a geometry-aware attention mechanism to refine object tracking across views MITracker achieves state-of-the-art results on MVTrack and GMTD datasets, setting a new benchmark for multi-view tracking. Watch the video below to see it in action! ???? Awesome work by: Mengjie Xu,?Yitao Zhu,?Haotian Jiang,?Jiaming Li, Zhenrong Shen,?Sheng Wang,?Haolin Huang,?Xinyu Wang,?Qing Yang,?Han Zhang,?Qian Wang ?? Stay tuned for more exciting developments and breakthroughs on the horizon! ? WISERLI YOLOvX OpenCV Roboflow Ultralytics Dr. Chandrakant Bothe Rohan Gupta Vishnu Mate Mohit Raj Sinha Prateeksha Tripathy Sinem ?elik Sharda Jadhav Neetu Shaw Anu Bothe Saurabh Tople Glenn Jocher Muhammad Rizwan Munawar Nicolai Nielsen Harpreet Sahota ?? Ritesh Kanjee Piotr Skalski Dragos Stan Arnaud Bastide Timothy Goebel Bharath kumar Sean Carnahan #ComputerVision #MultiViewTracking #CVPR2025 #DeepLearning #YOLOvX #AI