most citedAdversarial Attacks and Defenses on Text-to-Image Diffusion Models: A Survey

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cs.CV2025

SCAP: Transductive Test-Time Adaptation via Supportive Clique-based Attribute Prompting

Chenyu Zhang, Kunlun Xu, Zichen Liu +2

Vision-language models (VLMs) encounter considerable challenges when adapting to domain shifts stemming from changes in data distribution. Test-time adaptation (TTA) has emerged as…

cs.CV2025

TRCE: Towards Reliable Malicious Concept Erasure in Text-to-Image Diffusion Models

Ruidong Chen, Honglin Guo, Lanjun Wang +3

Recent advances in text-to-image diffusion models enable photorealistic image generation, but they also risk producing malicious content, such as NSFW images. To mitigate risk, con…

cs.CV2024

HoVLE: Unleashing the Power of Monolithic Vision-Language Models with Holistic Vision-Language Embedding

Chenxin Tao, Shiqian Su, Xizhou Zhu +8

The rapid advance of Large Language Models (LLMs) has catalyzed the development of Vision-Language Models (VLMs). Monolithic VLMs, which avoid modality-specific encoders, offer a p…

cs.CV2024

Self-supervised Monocular Depth and Pose Estimation for Endoscopy with Latent Priors

Ziang Xu, Bin Li, Yang Hu +4

Accurate 3D mapping in endoscopy enables quantitative, holistic lesion characterization within the gastrointestinal (GI) tract, requiring reliable depth and pose estimation. Howeve…

cs.CV2024

A New People-Object Interaction Dataset and NVS Benchmarks

Shuai Guo, Houqiang Zhong, Qiuwen Wang +6

Recently, NVS in human-object interaction scenes has received increasing attention. Existing human-object interaction datasets mainly consist of static data with limited views, off…