There is something deep in our nature that is always fascinated by transformations. Artificial intelligence (AI) made it possible for just about anyone with internet access to instantly swap faces of people. And the results are now more realistic than they have ever been. By using the best AI face swap tools, the results are now more realistic than they have ever been. Whether you want to drop your face into a movie scene, create viral social content, or build personalized marketing campaigns at scale, the best AI face swap tools in 2026 can pull it off in seconds. This guide cuts through the noise and ranks the 10 best face swap AI options right now. Quick Comparison: Top Face Swap AI Tools by VentureBurn | Face Swap Tools | Supported Formats | Starting Price | Processing Speeds | Watermark on Free Plan | Best For | | JPG, PNG, WEBP, MP4, GIF | $9.99/month | Fast (< 10s photos) | Yes | Video face swap. | | JPG, PNG, WEBP, MP4 | Free plan, $5.99 | Fast (10-15 seconds) | No | Batch & Multi-Face Images | | JPG, PNG, MP4, GIF | Free, $3.99/week | Instant | Yes | Mobile face swap | | JPG, PNG, MP4 | Free, $6.90/month | Fast (5-10 seconds) | Yes | Quick & seamless photo swaps | | JPG, PNG, WEBP, MP4 | $9/month | Real time | No | Professional image optimization | | JPG, PNG, MP4, M4V | Free, $9.99/month | Medium | Yes | Corporate video editing | | JPG, PNG, MP4 | Free, $10/month | Fast (10 seconds) | No | Creative marketing | | JPG, PNG, WEBP | Free, $4.99/month | Medium (10-60 seconds) | Yes | Stylized images & avatars | | JPG, PNG, MP4 |
May 30, 2026 · via ventureburn.com
NEW DELHI: Marking a major milestone for India’s digital public infrastructure, the Digi Yatra app has facilitated more than 10 crore seamless journeys across airports in the country. The facial recognition based system enables passengers to enter airports without the need for physical documents. According to an official release, the app has recorded more than 2.4 crore downloads across iOS and Android platforms since its launch. “The platform stands as one of the most successful digital innovations in global aviation today,” it said. By replacing manual document verification, the platform has reduced average airport entry processing time from 15 seconds to just five seconds per passenger. This faster throughput has significantly optimised terminal infrastructure, reduced congestion and minimised manual processing overheads. “Furthermore, by eliminating physical boarding passes, the initiative supports environmental sustainability by saving thousands of sheets of paper daily across participating airports,” the release added. Reflecting on the milestone, Civil Aviation Minister Ram Mohan Naidu said, “It reflects the growing trust passengers are placing in seamless, paperless and contactless travel. The scale of Digi Yatra’s adoption comes at a critical juncture. Daily domestic passenger traffic, which averaged below 2 lakh passengers in 2014, has now crossed the 5 lakh mark on numerous occasions over the last three years. “The annual passenger traffic across Indian airports is projected to reach 50 crore by 2030 and double to nearly 100 crore by 2040. To effectively manage this exponential growth, we are adopting multiple digital solutions such as Digi Yatra, Self-Baggage Drop Facility, augmentation of Air Traffic Control automation systems, the AirSewa portal for grievance redressal and AI powered digital twins to optimise airport operations.” Naidu added, “While many nations continue to evaluate the large scale deployment of biometric passenger processing, India has successfully operationalised and scaled Digi Yatra within a remarkably
May 30, 2026 · via newindianexpress.com
The Mandaue City Police Office, led by Col. Cirilo Acosta Jr., is urging the City Council to require local businesses to install high-definition CCTV cameras with facial recognition capabilities. The proposed ordinance amendments aim to improve criminal investigations by addressing low-quality security footage and establishing clearer, faster procedures for law enforcement to access private surveillance recordings. Mandaue City Mayor Thadeo Jovito “Jonkie” Ouano expressed support for the technology-driven initiative, while the City Council plans to conduct consultations to balance public safety with business interests. THE Mandaue City Police Office (MCPO) is urging the City Council to amend the City’s existing closed-circuit television (CCTV) ordinance to require business establishments to install high-definition surveillance cameras with facial recognition capabilities to strengthen crime prevention and improve criminal investigations. Col. Cirilo Acosta Jr., MCPO director, said the proposed amendments seek to modernize the city’s surveillance system and address recurring challenges investigators face when reviewing low-quality security footage from private establishments. Acosta said clearer and more advanced CCTV systems would significantly improve the ability of law enforcement agencies to identify suspects, reconstruct incidents and gather evidence during investigations. “The goal is to enhance public safety and make criminal investigations more efficient. Many cases could be resolved more quickly if authorities have access to high-quality video footage that clearly captures the identities of individuals involved,” Acosta said. Ordinance review The City Council is reviewing the proposal, with legislators checking the existing ordinance to determine the necessary amendments to strengthen its implementation. Under the proposed changes, business establishments throughout the city, particularly large commercial entities, must upgrade their security infrastructure to high-definition cameras with facial recognition technology. Police officials believe this technology enables investigators to identify persons of interest more rapidly and improves overall crime detection. Aside from upgrading camera standards, the proposal seeks to streamline police
May 30, 2026 · via sunstar.com.ph
How to Register New SIM Card Using Biometric Recognition Reporter May 30, 2026 | 06:36 pm TEMPO.CO, Jakarta - Indonesia is set to roll out SIM (subscriber identity module) card registration using facial biometric recognition starting July 1, 2026, as confirmed by the Digital Ecosystem DG at the Ministry of Communication and Digital (Komdigi), Edwin Hidayat Abdullah. Consumers can purchase SIM cards at various offline stores or online shops. "You can purchase a phone number anywhere, either in a store or web-based (mobile operator)," Edwin said in a virtual press conference in Jakarta on Friday, May 29, 2026. After getting their new SIM cards, consumers can activate the card through the mobile operator's application. The consumer then enters their National Identity Number (NIK). "The next step differs for each mobile operator. Some use PUK (Personal Unlocking Key), some use numbers. After that, an OTP (One-Time Password) will be generated," he said. After, consumers will be directed to complete face recognition, which will then be verified by the Directorate of Population and Civil Registration (Dukcapil). If the facial accuracy is 96 percent with the NIK identity, the verification process will be completed. "Then a notification will appear, showing that the verification is complete," Edwin said. Edwin claimed that the registration process takes an average of less than 1 minute, based on trials conducted by Komdigi. "I have observed hundreds of processes across various regions starting from Jakarta, Java, Central Java, East Java, West Java, Sumatra, West Sumatra, Aceh, Kalimantan," he said, citing Yogyakarta as the region with shortest processing time. Approximately 1.6 to 1.7 million users have used this technology since the trial began in January 2026. According to Edwin, three mobile operators have implemented the facial recognition system during the trial period, namely Telkomsel, Indosat, and XLSmart. Based on consumer
May 30, 2026 · via en.tempo.co
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May 30, 2026 · via youtube.com
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May 30, 2026 · via theregister.com
A thorough comparison of classical and quantum machine learning models using the MNIST dataset reveals key differences in performance. Sudip Vhaduri and colleagues at University of Alabama evaluated accuracy, runtime, parameter count, and memory requirements across varying feature dimensions and sample sizes. The findings demonstrate that quantum support vector machines consistently achieve higher accuracy than classical support vector machines. Furthermore, quantum convolutional neural networks exhibit sharply improved parameter and memory efficiency, requiring up to 94% fewer parameters and 75% less memory, although with increased runtime. This multidimensional benchmarking study highlights the potential for quantum models to outperform classical models, particularly with higher dimensionality or larger datasets, and provides valuable insights into practical operating parameters for quantum machine learning. Quantum neural networks exhibit substantial gains in parameter efficiency and classification Quantum Convolutional Neural Networks (QCNNs) now require approximately 94% fewer parameters and 75% less memory than Classical Convolutional Neural Networks (CCNNs) at higher feature counts, a reduction previously unattainable with classical deep learning approaches. This efficiency unlocks the potential for deploying complex image recognition models on resource-constrained devices, overcoming a significant barrier in fields like automated transport and cybersecurity. Achieving comparable classification accuracy exceeding 0.96 with 64 features and 60,000 samples, the QCNN’s reduced memory footprint represents a substantial advancement in model scalability. The MNIST dataset, comprising 70,000 labelled grayscale images of handwritten digits, served as the benchmark for this comparison. Classical convolutional neural networks typically rely on numerous weighted connections between layers, leading to a high parameter count and substantial memory requirements, particularly when dealing with high-resolution images or complex feature extraction. QCNNs, leveraging principles of quantum superposition and entanglement, represent data in a fundamentally different way, allowing for a more compact and efficient representation. This is achieved through the use of quantum circuits that perform operations on qubits, the
May 30, 2026 · via quantumzeitgeist.com
SAN FRANCISCO, CA, May 30, 2026 /24-7PressRelease/ -- In March 2026, the U.S. Federal Trade Commission alleged that OkCupid gave a third-party facial-recognition company access to nearly three million user photos, along with location and other personal information, without properly informing users or giving them a meaningful chance to opt out. For the dating-app industry, that should be a breaking point. For LGBTQ+ users, it is more than another privacy scandal. It is a warning. A dating profile is not ordinary data. It can contain a face, a location pattern, a sexual orientation, a private conversation, a hidden identity, a health disclosure, a social risk, a family risk, or even legal risk. In the wrong hands, it can become evidence. It can become leverage. It can become exposure. That is the reality u2nite was built to confront. Developed by Wildtrolls Ltd. & Co. KG in Munich, u2nite is a privacy-first LGBTQ+ dating and social app designed for people who want connection without becoming part of a hidden data economy. Its core idea is simple: your identity should never become a product. The problem is not theoretical. In recent years, dating apps have moved from being social tools into data-rich identity platforms. They know who people are attracted to, where they move, when they are active, who they contact, what they share, and sometimes what they fear revealing publicly. That kind of information is powerful. It is also dangerous. The OkCupid case is especially significant because it connects dating privacy directly with facial recognition and AI. Photos uploaded for connection were allegedly made available to a company working in biometric technology. Whether such data is used for AI training, identity analysis, analytics, research or other commercial purposes, the core question remains the same: did the user truly understand where intimate data
May 30, 2026 · via 24-7pressrelease.com
Yoti challenges academic research, invites independent audit of age assurance platform Yoti has publicly challenged research presented by academics from the Georgia Institute of Technology and the University of California, Irvine, and invited an independent cybersecurity audit of its age assurance platform in an effort to rebut claims about how it handles user data. The dispute highlights growing scrutiny of age assurance technologies as governments increasingly require age checks for access to online content and services. It also marks an unusual move by a leading provider, which is responding to criticism not only with public rebuttals but by offering independent verification of its systems. Researchers presenting at the IEEE Symposium on Security and Privacy argued that Yoti’s age verification process transmits personal information to third- and fourth-party companies, including credit card providers, geolocation services and data brokers. An article from the blog of Georgia Tech’s College of Computing summarizes: “The researchers found that the information being shared can be used to identify and track devices. For example, a single verification attempt may transmit a user’s facial image, IP address, and device fingerprint to credit card companies.” Yoti CEO Robin Tombs rejected those claims in an open letter, calling allegations that facial image data is shared with third parties “wholly false.” Rather than limiting its response to public criticism, Yoti has challenged the researchers to nominate an independent cybersecurity expert to review the company’s technology and verify how user data is handled. Yoti says claims are ‘wholly false’ “The allegation that Yoti’s age verification platforms transmits facial image data to any third party is wholly false,” says Yoti CEO Robin Tombs, in an open letter that calls for a redaction of the articles in which the claim is made, and a public apology from the two U.S. schools. “Our systems are
May 30, 2026 · via biometricupdate.com
BuzzFeed GamesOnly People With Elite Pattern Recognition Can Solve This Color Puzzle Called HuedokuHuedoku #33! It’s Friday — go out on a high note. 🌈🎉Posted 7 hours agocommentFacebookPinterestLinkby Crystal RoBuzzFeedBuzzFeed StaffHi, I’m Crystal, a Senior Editor based in Los Angeles and creator of BuzzFeed’s “That Got Dark” newsletter. Huedoku is a daily color puzzle with simple rules and a satisfying solve. It's like sudoku, but with colors instead of numbers. Sign up here to get notified every time we publish a new Huedoku! Have a great weekend — Huedoku #34 drops Monday! 🌈 🌈 New Huedoku drops every weekday at 4:00 a.m. PT / 7:00 a.m. ET. 🧩🗂️ Huedoku Archive — Every past puzzle, all in one place! Comments
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May 30, 2026 · via buzzfeed.com
India is deploying facial recognition and algorithmic policing tools at scale without a governing framework, where unaddressed opacity and discriminatory error risk making efficiency come at the cost of justice Artificial intelligence and biometric tools have moved from proposal to practice in Indian law enforcement, a shift that has been underway since at least 2017-2018 and has only gained urgency over time. After the 2020 Northeast Delhi riots, investigators turned to facial recognition technology to identify those involved. The results were uneven. In one case, a man spent four and a half years in custody before securing bail. His detention rested substantially on an 80 percent similarity score generated by Facial Recognition Technology (FRT) from a CCTV frame. Delhi Police deployed FRT in more than 750 riot investigations, yet over 80 percent of those that reached a verdict ended in acquittal or discharge. The state has structural reasons to lean on automation. The India Justice Report records a police-to-population ratio stalled at 155 per 100,000, well short of the United Nations benchmark of 222. Bihar manages roughly 81 per 100,000, and 22 percent of sanctioned posts remain vacant nationally. In an environment of chronic under-resourcing, algorithmic assistance is easily presented as an administrative remedy. These methods are far from foolproof; over-dependence risks blind policing. Algorithmic policing in India has expanded without an anchoring statute. The Project Panoptic tracker documents 170 facial recognition systems commissioned across agencies, though only around 20 are operational, at a cumulative outlay of ₹1,513 crore. Punjab’s PAIS searches over 390,000 records and 84,000 voice samples, Uttar Pradesh’s Trinetr holds more than 900,000 records, and Telangana issues TSCOP units to officers for real-time biometric matching. In 2018, under the Delhi High Court’s direction in Sadhan Haldar v. NCT of Delhi, the police acquired FRT for a single
May 30, 2026 · via orfonline.org
Plant Identifier Turns A Photo Into Instant Botanical Knowledge Ellen Smith — May 29, 2026 — Tech References: apps.apple Walking past unknown plants and trees often leaves people curious but without answers -- Plant Identifier removes that uncertainty by instantly identifying plants from a simple photo. Users can snap a picture or upload an image from their gallery, and the AI quickly analyzes it to determine the plant species. This makes it easy to learn about nature in real time without needing expert knowledge. The app acts like a pocket botanist, helping users understand the environment around them with minimal effort. It turns everyday walks into opportunities for discovery and learning. Plant Identifier is aimed at nature enthusiasts, gardeners, and curious users. By combining image recognition with botanical data, it makes plant identification fast and accessible. Image Credit: Plant Identifier Users can snap a picture or upload an image from their gallery, and the AI quickly analyzes it to determine the plant species. This makes it easy to learn about nature in real time without needing expert knowledge. The app acts like a pocket botanist, helping users understand the environment around them with minimal effort. It turns everyday walks into opportunities for discovery and learning. Plant Identifier is aimed at nature enthusiasts, gardeners, and curious users. By combining image recognition with botanical data, it makes plant identification fast and accessible. Image Credit: Plant Identifier Trend Themes - Real-time Visual Recognition — Instant image-based identification of plants enables automated, context-aware information delivery that can redefine mobile learning and field diagnostics. - Augmented Botanical Education — By overlaying species data and ecological facts onto real-world views, the learning experience for amateurs and students can shift from classroom-bound to experiential and location-specific. - Citizen Science Data Integration — Crowdsourced plant observations from many
May 30, 2026 · via trendhunter.com
Xactus, a fintech company that provides credit verification services for the mortgage industry, has acquired Mortgage Credit Link (MCL) from MeridianLink, a platform designed to streamline order fulfillment for credit and data verification. Now called XedaLink, the business segment will be structured as a subsidiary of Xactus but will continue to operate within its existing framework and will keep its distinct client and partner base intact. Pennsylvania-based lender-servicer Newrez announced the launch of Rezi Mortgage Assistant, an AI-powered mortgage guide built directly into ChatGPT. The tool is crafted to provide plain-language mortgage and home equity responses to consumers, with the AI model trained on Newrez’s underwriting guidelines, lending policies and educational content. Newrez also announced a partnership with Matic to integrate its digital insurance marketplace into Newrez’s HomeHub portal. The integration is designed to enable Newrez customers to compare personalized homeowners insurance options and receive proactive quotes. GO Mortgage announced the launch of a third-party origination channel. The wholesale platform will be led by Rob Saunders, who has been named executive vice president of TPO production. The company noted that the platform will be rolled out to a select group of broker partners over the next two months, a move designed to evaluate performance at scale before expanding nationally. Planet has expanded its offerings to include non-agency loans, including a suite of non-qualified mortgage (non-QM) products featuring alternative income and debt-service coverage ratio (DSCR) options. The Connecticut-based lender had previously introduced a non-agency correspondent pilot at the tail end of 2025, noting in a recent press release that it has seen “significant adoption from its nearly 800 lending partners.” Panorama Mortgage Group, which celebrated its 20th anniversary this month, has rebranded as SimplyPMG. The move unifies the Alterra Home Loans and Travisa Financial channels under a single brand, with the
May 29, 2026 · via scotsmanguide.com
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May 29, 2026 · via youtube.com
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May 29, 2026 · via instagram.com
JACKSONVILLE, Fla. — The Jacksonville Sheriff’s Office is facing renewed questions over its use of artificial intelligence facial recognition technology after a second man said the system wrongly identified him as a suspect, leading to three months behind bars. Only on Action News Jax, Jalil Richardson, a Charlotte, North Carolina father of 10, said he was extradited to Jacksonville and spent nearly three months in jail for a car theft investigators later determined he did not commit. >>> STREAM ACTION NEWS JAX LIVE <<< “It’s overwhelming and it’s devastating and it’s outrageous,” Richardson told Action News Jax. According to a Jacksonville police report, investigators used Automated Facial Recognition, or AFR, to compare surveillance footage from a Publix parking lot theft case to Richardson’s photo. Jasmine Jackson, Richardson’s wife, said officers told them the software identified her husband as an “85% match.” “He said, ‘Jalil came back as close as 85% and that’s the reason why he charged Jalil with the crime,’” Jackson said. The investigation began April 2, 2025, when a victim told JSO he unknowingly purchased a stolen car from a man he met at a Publix on Baymeadows Road. Police later showed the victim a photo lineup, where he identified Richardson as the suspect. But timecards later proved Richardson was at work in North Carolina when the alleged crime happened nearly 400 miles away in Jacksonville. “None of the people that she had even came close to looking like my husband,” Jackson said. Richardson said he first learned about the warrant after calling police to his home in Charlotte for an unrelated disturbance. “When they arrived, they informed me they had a warrant for me out in Jacksonville and I was incarcerated for 33 days in Mecklenburg County,” Richardson said. “They extradited me to Florida after 33 days
May 29, 2026 · via actionnewsjax.com
May 29, 2026 Ice Hockey Video Analytics Using Deep Learning Title: Ice Hockey Video Analytics Using Deep Learning Presenter: David A. Clausi, University of Waterloo Date: June 3rd, 2026 at 10:30am to 11:30am Location: ENC 201 Ice hockey presents a uniquely challenging environment for computer vision and video analytics due to its high player density, rapid motion, frequent occlusions, complex interactions, and continuous gameplay. In this talk, I will present a research program focused on advancing automated understanding of ice hockey through modern video analytics techniques. The presentation will cover methods for homography, multi-object detection and tracking, player and puck localization, action recognition from broadcast video. Emphasis will be placed on the challenges associated with unconstrained sports video, including camera motion, scale variation, severe occlusion, and limited annotated training data. This work demonstrates how advances in AI and video understanding are enabling new forms of automated sports intelligence and opening opportunities for impactful interdisciplinary research collaborations. -- David A. Clausi (PEng, FCAE, FEIC, FIEEE) is a Professor in Systems Design Engineering and University Research Chair at the University of Waterloo who specializes in the field of Intelligent Systems. After earning his Ph.D. (1996) he worked in medical imaging at Mitra Imaging (Waterloo). He started his academic career in 1997 as an Assistant Professor in Geomatics Engineering at the University of Calgary. Dr. Clausi was the Associate Dean - Research & External Partnerships in the Faculty of Engineering (2018-2024). Prof. Clausi has many contributions, conducting research primarily in remote sensing, computer vision, image processing, and sports analytics. He has published extensively, has been an Associate Editor for leading journals, received many scholarships, paper awards, research and teaching excellence awards and his efforts have led to successful commercial implementations.
May 29, 2026 · via ucalgary.ca
This is part three of the Principal Components in TypeScript series, and it focuses on the application of PCA to a visual explanation of vision neural networks. Principal Components in TypeScript Previous parts: Part 1: https://hackernoon.com/principal-components-in-typescript-part-1 Part 2: https://hackernoon.com/principal-components-in-typescript-part-2-how-pca-actually-works-under-the-hood Part 1: https://hackernoon.com/principal-components-in-typescript-part-1 https://hackernoon.com/principal-components-in-typescript-part-1 Part 2: https://hackernoon.com/principal-components-in-typescript-part-2-how-pca-actually-works-under-the-hood https://hackernoon.com/principal-components-in-typescript-part-2-how-pca-actually-works-under-the-hood If you need a TL;DR, just go through the code or grab the package here on npm If you need a TL;DR, just go through the code or grab the package here on npm here on npm Not a Code Blog This is not a code blog. There’s no easy copy-paste solution here. If that’s what you want, go straight to the source code above. Now this post attempts to use PCA in a totally different direction compared to the vanilla dimensionality reduction or to data compression discussed in the earlier posts. Basically, for this post, I'm going to walk you through how to attempt to uncover insights from CNN features. But before that, we must answer a very important question. Are CNNs outdated? Is this the age of Transformers? Are CNNs outdated? Is this the age of Transformers? Not exactly, as ConvNext proved in 2022, CNNs still have a role to play in most vision tasks, as well as being pretty much the only option for highly performant edge deployment on extremely compute-limited devices. ConvNext Since we have now answered the above question unconvincingly, let us attempt to figure out how to do it. A note of warning, while I have specified Typescript here (since that is what my library is written in), we still do not have a convincing CNN solution in pure JS or Typescript. The good news, I am working on one, and even though it isn't close to release, I am going to leave the link to my
May 29, 2026 · via hackernoon.com
Figures Abstract In the process of urban kitchen waste sorting, robots often encounter issues such as slipping and empty grabs when attempting to grasp dirty waste objects like plastic bottles and glass bottles. This paper proposes a garbage grasping framework based on the Channel Exchange Generative Residual Inference Network (CE-GR-NET), which synthesizes optimal grasping trajectories through the fusion of hierarchical visual features. The object detection network identifies and locates recyclable bottles among solid waste, while CE-GR-NET uses RGB and depth images to generate grasping points for plastic recyclable bottles. Experimental results show that, on the Cornell Grasping Dataset, the proposed method achieves good inference performance and fast inference speed in single-object solid waste scenarios, ultimately generating grasping boxes for plastic recyclable bottles in RGB images. On the self-constructed multi-source urban kitchen waste images, the proposed method generates grasping boxes for targets and regresses the corresponding object categories simultaneously, achieving an image-based model accuracy of 96.03%, an object-based model accuracy of 94.40%, and a grasping object classification accuracy of 97.87%. Citation: Xiao X, Liu D, Qin H (2026) A grasp point generation algorithm for waste handling based on a generative reasoning network. PLoS One 21(5): e0349864. https://doi.org/10.1371/journal.pone.0349864 Editor: Marco Antonio Moreno-Armendariz, Instituto Politecnico Nacional, MEXICO Received: November 15, 2025; Accepted: May 6, 2026; Published: May 29, 2026 Copyright: © 2026 Xiao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability: All relevant data are within the paper. Funding: This work was supported in part by the Project of the Hunan Provincial Natural Science Foundation (2026JJ90097), the Scientific Research Fund of Hunan Provincial Education Department (25A0672), and the Research and Practice of the
May 29, 2026 · via journals.plos.org
CHARLOTTE — Court documents provide new details about a shooting inside a northwest Charlotte Walmart.
Channel 9 reported on Thursday that the Charlotte-Mecklenburg Police Department arrested 17-year-old Xavier Tirado for reportedly shooting another 17-year-old on May 21 at the Walmart on Callabridge Court.
The affidavit says surveillance video shows the person who was shot was reaching into his waistband and grabbing a gun. As this happened, shots were fired at the victim.
The shooting wasn’t captured on video, but CMPD says cameras caught Tirado and a second suspect fleeing the store.
CMPD says investigators used NCDMV facial recognition technology to identify Tirado as the suspect.
He was charged with attempted murder and held on a $25,000 bond. He posted that bond the next morning and was released from jail.
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May 29, 2026 · via wsoctv.com