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20222026
most citedDiffusionInst: Diffusion Model for Instance Segmentation

23 citations · 35 across the 32 of their papers we have counts for

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Showing 2026 · cs.CVShow all

8 papers · 2 filters

cs.CV2026

Learning Continuous Source Responses For Generalizable AI-Generated Image Detection

Manni Cui, Ruiqi Liu, Zijian Yu +8

Advances in image generation have made synthetic images increasingly difficult to distinguish from real photographs, raising concerns about the trustworthiness of visual media. Exi…

cs.CV2026

Source-Face Authenticity Detection for 3D Gaussian Heads Reconstructed from a Single Portrait: A Benchmark and Dedicated Detector

Yujie Gao, Zijian Yu, Yan Hong +2

Recent advances in single-image 3D Gaussian head reconstruction have enabled highly realistic and freely renderable digital heads from a single portrait. However, reconstruction an…

cs.CV2026

GAP-SAM: A Global Artifact Prior for Generalizable AI-Generated Image Manipulation Localization

Haozhen Yan, Siyuan Shan, Zijian Yu +4

AI-generated image manipulation localization identifies edited pixels, but its OOD performance lags behind image-level detection partly because pixel supervision entangles forensic…

cs.CV2026

Enhancing Localized Reasoning for Long Video Understanding via Efficient Segment-to-Video Supervision

Beibei Zhang, Chao Xu, Jun Lan +4

Though Multimodal Large Language Models (MLLMs) have shown impressive potential in video understanding, long video understanding (LVU) remains challenging since distracting noise i…

cs.CV2026

ArmorOCR: Grounded Adversarial Visual Perception via Observation-Transferred Self-Distillation

Linhan Cao, Siyuan Li, Jun Lan +8

Large multimodal models (LMMs) have demonstrated strong OCR recognition capabilities, yet remain vulnerable to adversarial visual text that is readable to humans but challenging fo…

cs.CV2026

Adaptive and Balanced Re-initialization for Long-timescale Continual Test-time Domain Adaptation

Yanshuo Wang, Jinguang Tong, Jun Lan +5

Continual test-time domain adaptation (CTTA) aims to adjust models so that they can perform well over time across non-stationary environments. While previous methods have made cons…

cs.CV2026

VTONGuard: Automatic Detection and Authentication of AI-Generated Virtual Try-On Content

Shengyi Wu, Yan Hong, Shengyao Chen +5

With the rapid advancement of generative AI, virtual try-on (VTON) systems are becoming increasingly common in e-commerce and digital entertainment. However, the growing realism of…

cs.CV2026

Generalizable and Adaptive Continual Learning Framework for AI-generated Image Detection

Hanyi Wang, Jun Lan, Yaoyu Kang +4

The malicious misuse and widespread dissemination of AI-generated images pose a significant threat to the authenticity of online information. Current detection methods often strugg…