3 citations · 3 across the 15 of their papers we have counts for
14 papers · 1 filter
InfraPatch: Cross-Task Targeted Grayscale Patch Attacks on Infrared-Adapted Vision-Language Models
Chengyin Hu, Dingyi Lu, Jiaju Han +5
Infrared vision-language models (IR-VLMs) have emerged as a promising paradigm for multimodal perception under low-visibility conditions, yet their robustness to targeted adversari…
Radar4D-VLM: Proposal-Grounded Temporal 4D Radar Reasoning Across Frozen Language Models
Jiaju Han, Xuemeng Sun, Qike Zhang +6
Vision-language models for autonomous driving primarily rely on cameras and LiDAR, leaving 4D radar largely unexplored as a standalone perceptual modality despite its robustness to…
QR-Structured Thermal Triggers for Targeted Semantic Attacks on Infrared Vision-Language Models
Xiang Chen, Yingying Zhao, Chao Li +7
Infrared vision-language models (IR-VLMs) extend thermal perception to open-vocabulary classification, image captioning, and visual question answering. However, their robustness to…
MonoIR-RS: Infrared Remote Sensing Vision-Language Learning with CLIP and VLM Adaptation
Jiaju Han, Ma Yaqi, Yahui Chai +8
Infrared remote-sensing imagery captures intensity structure, object-background contrast, and illumination-invariant cues often invisible in RGB imagery. Yet, most remote-sensing v…
Exposing Vulnerabilities in Visible-Infrared VLMs: A Unified Geometric Adversarial Framework with Cross-Task Transferability
Xiang Chen, Yuxian Dong, Chao Li +6
Vision-language models (VLMs) have achieved strong performance across diverse multimodal tasks, but their adversarial robustness in visible-infrared (VIS-IR) scenarios remains unde…
When Surfaces Lie: Exploiting Wrinkle-Induced Attention Shift to Attack Vision-Language Models
Chengyin Hu, Xuemeng Sun, Jiaju Han +5
Visual-Language Models (VLMs) have demonstrated exceptional cross-modal understanding across various tasks, including zero-shot classification, image captioning, and visual questio…
Revealing Physical-World Semantic Vulnerabilities: Universal Adversarial Patch for Infrared Vision-Language Models
Chengyin Hu, Yuxian Dong, Yikun Guo +8
Infrared vision-language models (IR-VLMs) are becoming important for semantic perception in low-visibility environments, yet their robustness to physical semantic attacks remains u…
A Semantic Decoupling-Based Two-Stage Rainy-Day Attack for Revealing Weather Robustness Deficiencies in Vision-Language Models
Chengyin Hu, Xiang Chen, Zhe Jia +4
Vision-Language Models (VLMs) are trained on image-text pairs collected under canonical visual conditions and achieve strong performance on multimodal tasks. However, their robustn…
VUGEN: Visual Understanding priors for GENeration
Xiangyi Chen, Théophane Vallaeys, Maha Elbayad +2
Recent advances in Vision-Language Models (VLMs) have enabled unified understanding across text and images, yet equipping these models with robust image generation capabilities rem…
DeLiVR: Differential Spatiotemporal Lie Bias for Efficient Video Deraining
Shuning Sun, Jialang Lu, Xiang Chen +5
Videos captured in the wild often suffer from rain streaks, blur, and noise. In addition, even slight changes in camera pose can amplify cross-frame mismatches and temporal artifac…
HumanOmni: A Large Vision-Speech Language Model for Human-Centric Video Understanding
Jiaxing Zhao, Qize Yang, Yixing Peng +8
In human-centric scenes, the ability to simultaneously understand visual and auditory information is crucial. While recent omni models can process multiple modalities, they general…
Facial Dynamics in Video: Instruction Tuning for Improved Facial Expression Perception and Contextual Awareness
Jiaxing Zhao, Boyuan Sun, Xiang Chen +1
Facial expression captioning has found widespread application across various domains. Recently, the emergence of video Multimodal Large Language Models (MLLMs) has shown promise in…
LLaVA-Octopus: Unlocking Instruction-Driven Adaptive Projector Fusion for Video Understanding
Boyuan Sun, Jiaxing Zhao, Xiang Chen +2
In this paper, we introduce LLaVA-Octopus, a novel video multimodal large language model. LLaVA-Octopus adaptively weights features from different visual projectors based on user i…
Face Aging via Diffusion-based Editing
Xiangyi Chen, Stéphane Lathuilière
In this paper, we address the problem of face aging: generating past or future facial images by incorporating age-related changes to the given face. Previous aging methods rely sol…