BestHub
Sign in
Tagged articles

deepfake detection

9 articles · Page 1 of 1
Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Aug 16, 2026 · Artificial Intelligence

Can We Still Trust Our Eyes as AI-Generated Content Becomes Indistinguishable?

As AI-generated images, audio, and video become increasingly realistic, traditional visual cues for spotting fakes fade, prompting a shift toward technical defenses—detection, watermarking, and provenance—and a structured personal verification process to maintain trust.

AI authenticityAI-generated mediacontent provenance
0 likes · 8 min read
Can We Still Trust Our Eyes as AI-Generated Content Becomes Indistinguishable?
Machine Heart
Machine Heart
Apr 10, 2026 · Artificial Intelligence

Ant AI Wins CVPR 2026 Challenge: A Powerful Countermeasure Against Deepfake Abuse

Amid rising deep‑fake misuse in entertainment, Ant Group’s AI Security Lab won the CVPR 2026 NTIRE Robust AIGC Image Detection challenge with a ROC AUC of 0.9723, presenting a DINOv3‑based robust detection framework, extensive multi‑source data, and novel augmentation and optimization techniques to combat AI‑generated abuse.

AIGCCVPR 2026DINOv3
0 likes · 10 min read
Ant AI Wins CVPR 2026 Challenge: A Powerful Countermeasure Against Deepfake Abuse
Sohu Tech Products
Sohu Tech Products
Oct 29, 2025 · Information Security

Why a New Multimodal AI Security Dataset Is Essential for Detecting Deepfakes

As multimodal AI models become capable of generating realistic images, videos, and audio, the OpenMMSec benchmark provides a comprehensive, open‑source dataset and evaluation metrics that help researchers and developers detect and localize AI‑generated forgeries across all three modalities, addressing emerging security challenges.

AI securityMultimodal DatasetOpenMMSec
0 likes · 18 min read
Why a New Multimodal AI Security Dataset Is Essential for Detecting Deepfakes
AntTech
AntTech
Jan 6, 2025 · Artificial Intelligence

2024 Security and Trusted AI Research Highlights from Alibaba, Tsinghua, Zhejiang, and Partner Institutions

This article presents sixteen peer‑reviewed research papers published in top conferences and journals in 2024, covering trusted AI, large‑model applications, network security, adversarial training, deep‑fake detection, secure inference, and related topics from collaborations among Alibaba, Tsinghua, Zhejiang, and other leading institutions.

AI securitySecure InferenceTrusted AI
0 likes · 27 min read
2024 Security and Trusted AI Research Highlights from Alibaba, Tsinghua, Zhejiang, and Partner Institutions
Baidu Geek Talk
Baidu Geek Talk
Oct 20, 2023 · Artificial Intelligence

Can Ignoring Identity Features Boost Deepfake Detection? A New Approach

This article analyzes the hidden "identity leakage" problem in deepfake detectors, proposes a novel algorithm that suppresses identity cues by focusing on local forged regions and multi‑scale facial manipulation, and demonstrates through extensive experiments that the method markedly improves generalization across unseen forgery techniques.

AI securitydeepfake detectionidentity leakage
0 likes · 13 min read
Can Ignoring Identity Features Boost Deepfake Detection? A New Approach
IT Services Circle
IT Services Circle
Apr 13, 2022 · Artificial Intelligence

Introducing DualStyleGAN, RQ‑VAE Transformer, and VFD: Recent CVPR 2022 Open‑Source Algorithms

Jack Cui presents three recently open‑sourced CVPR 2022 algorithms—DualStyleGAN for high‑resolution portrait style transfer, RQ‑VAE Transformer for improved text‑to‑image generation, and VFD for deep‑fake detection—detailing their functionality, usage options, and providing links to code repositories and demo platforms.

AIGenerative Modelsdeepfake detection
0 likes · 5 min read
Introducing DualStyleGAN, RQ‑VAE Transformer, and VFD: Recent CVPR 2022 Open‑Source Algorithms
NetEase Smart Enterprise Tech+
NetEase Smart Enterprise Tech+
Sep 2, 2021 · Artificial Intelligence

How AI Detects Video Deepfakes: Techniques, Challenges, and Real-World Solutions

This article explores the rapid rise of AI‑generated video deepfakes, examines the four main manipulation techniques, discusses the inherent security risks, and presents NetEase Yidun’s comprehensive detection framework—including face‑detection‑based classification, semi‑supervised learning, feature fusion, and model distillation—to combat content‑security threats.

AI securitycomputer visiondeepfake detection
0 likes · 12 min read
How AI Detects Video Deepfakes: Techniques, Challenges, and Real-World Solutions
NetEase Smart Enterprise Tech+
NetEase Smart Enterprise Tech+
Aug 9, 2021 · Artificial Intelligence

How NetEase’s 2021 Audio‑Video Tech Conference Shaped the Future of AI‑Driven Media

The 2021 NetEase "Eye‑Opening, Sound‑Immersive" audio‑video technology conference gathered experts from NetEase’s divisions to showcase AI‑powered video processing, deep‑fake detection, immersive audio, and innovative media solutions, drawing over 54,000 viewers and promising ongoing video releases for the community.

AIaudioconference
0 likes · 8 min read
How NetEase’s 2021 Audio‑Video Tech Conference Shaped the Future of AI‑Driven Media
Kuaishou Tech
Kuaishou Tech
Apr 6, 2021 · Artificial Intelligence

Frequency-Aware Feature Learning with Single-Center Loss for Face Forgery Detection

Researchers from USTC and Kuaishou propose a frequency‑aware feature learning framework that combines a data‑driven adaptive frequency module with a novel single‑center loss, achieving state‑of‑the‑art performance on deepfake detection while addressing class‑distribution challenges.

AI securitycomputer visiondeepfake detection
0 likes · 7 min read
Frequency-Aware Feature Learning with Single-Center Loss for Face Forgery Detection