2 citations · 3 across the 8 of their papers we have counts for
12 papers · 1 filter
LoRC: Detecting AI-Generated Images via Low-Rank Collapse in Semantic Residuals
Haozhen Yan, Ruoxin Chen, Jiahui Zhan +6
Modern generators faithfully model macroscopic semantics, producing synthetic images that appear highly realistic. Consequently, decisive forensic cues reside in subtle non-semanti…
Defake-o3: From Speculative Rationales to Verifiable Evidence for Explainable AIGI Detection
Bowen Deng, Jiahui Zhan, Yikun Ji +2
The rapid progress of image generation models calls for AI-generated image (AIGI) detectors that are not only accurate but also explainable and reliable. While MLLM-based detectors…
DirectTryOn: One-Step Virtual Try-On via Straightened Conditional Transport
Xianbing Sun, Jiahui Zhan, Liqing Zhang +1
Recent diffusion- and flow-based VTON methods achieve strong results with pretrained generative models, but their reliance on multi-step sampling incurs high inference cost, while…
Towards Source-Aware Object Swapping with Initial Noise Perturbation
Jiahui Zhan, Xianbing Sun, Xiangnan Zhu +4
Object swapping aims to replace a source object in a scene with a reference object while preserving object fidelity, scene fidelity, and object-scene harmony. Existing methods eith…
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…
GAMMA: Generalizable Alignment via Multi-task and Manipulation-Augmented Training for AI-Generated Image Detection
Haozhen Yan, Yan Hong, Suning Lang +6
With generative models becoming increasingly sophisticated and diverse, detecting AI-generated images has become increasingly challenging. While existing AI-genereted Image detecto…
FW-VTON: Flattening-and-Warping for Person-to-Person Virtual Try-on
Zheng Wang, Xianbing Sun, Shengyi Wu +5
Traditional virtual try-on methods primarily focus on the garment-to-person try-on task, which requires flat garment representations. In contrast, this paper introduces a novel app…
DS-VTON: An Enhanced Dual-Scale Coarse-to-Fine Framework for Virtual Try-On
Xianbing Sun, Yan Hong, Jiahui Zhan +5
Despite recent progress, most existing virtual try-on methods still struggle to simultaneously address two core challenges: accurately aligning the garment image with the target hu…
Robustness in AI-Generated Detection: Enhancing Resistance to Adversarial Attacks
Sun Haoxuan, Hong Yan, Zhan Jiahui +6
The rapid advancement of generative image technology has introduced significant security concerns, particularly in the domain of face generation detection. This paper investigates…
COCO-Inpaint: A Benchmark for Detecting and Localizing Inpainting-Based Image Manipulations
Haozhen Yan, Yan Hong, Jiahui Zhan +5
Recent advances in image manipulation have enabled highly photorealistic content generation, but also lowered the barrier to arbitrary editing, raising concerns about multimedia au…
Towards Explainable Fake Image Detection with Multi-Modal Large Language Models
Yikun Ji, Yan Hong, Jiahui Zhan +6
Progress in image generation raises significant public security concerns. We argue that fake image detection should not operate as a "black box". Instead, an ideal approach must en…
High-Quality 3D Head Reconstruction from Any Single Portrait Image
Jianfu Zhang, Yujie Gao, Jiahui Zhan +4
In this work, we introduce a novel high-fidelity 3D head reconstruction method from a single portrait image, regardless of perspective, expression, or accessories. Despite signific…