collaborators

15 papers

cs.CV2026

SACE: Concept Erasure at the Semantic Singularity in Visual Autoregressive Models

Siya Yang, Nanxiang Jiang, Zhaoxin Fan +1

The rapid progress of visual autoregressive (VAR) models has unlocked a transformative frontier for high-fidelity text-to-image synthesis, while heightening concerns over the safet…

cs.CV2026

NTIRE 2026 The Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results

Xin Li, Yeying Jin, Suhang Yao +95

This paper presents an overview of the NTIRE 2026 Second Challenge on Day and Night Raindrop Removal for Dual-Focused Images. Building upon the success of the first edition, this c…

cs.CV2026

Z-Erase: Enabling Concept Erasure in Single-Stream Diffusion Transformers

Nanxiang Jiang, Zhaoxin Fan, Baisen Wang +8

Concept erasure serves as a vital safety mechanism for removing unwanted concepts from text-to-image (T2I) models. While extensively studied in U-Net and dual-stream architectures…

cs.CV2026

LatentStealth: Unnoticeable and Efficient Adversarial Attacks on Expressive Human Pose and Shape Estimation

Zhiying Li, Guanggang Geng, Yeying Jin +4

Expressive human pose and shape estimation (EHPS) plays a central role in digital human generation, particularly in live-streaming applications. However, most existing EHPS models…

cs.CV2026

Mosaic: Multimodal Jailbreak against Closed-Source VLMs via Multi-View Ensemble Optimization

Yuqin Lan, Gen Li, Yuanze Hu +6

Vision-Language Models (VLMs) are powerful but remain vulnerable to multimodal jailbreak attacks. Existing attacks mainly rely on either explicit visual prompt attacks or gradient-…

cs.CV2026

Erased, But Not Forgotten: Erased Rectified Flow Transformers Still Remain Unsafe Under Concept Attack

Nanxiang Jiang, Zhaoxin Fan, Enhan Kang +6

Recent advances in text-to-image (T2I) diffusion models have enabled impressive generative capabilities, but they also raise significant safety concerns due to the potential to pro…