27 citations · 64 across the 23 of their papers we have counts for
9 papers · 1 filter
Towards Robustness against Typographic Attack with Training-free Concept Localization
Bohan Liu, Wenqian Ye, Guangzhi Xiong +3
Models trained via Contrastive Language-Image Pretraining (CLIP) serve as the foundational vision encoders for most modern Large Vision Language Models (LVLMs). Despite their wides…
Medical Video Generation for Disease Progression Simulation
Xu Cao, Kaizhao Liang, Kuei-Da Liao +7
Modeling disease progression is crucial for improving the quality and efficacy of clinical diagnosis and prognosis, but it is often hindered by a lack of longitudinal medical image…
Benchmarking Spurious Bias in Few-Shot Image Classifiers
Guangtao Zheng, Wenqian Ye, Aidong Zhang
Few-shot image classifiers are designed to recognize and classify new data with minimal supervision and limited data but often show reliance on spurious correlations between classe…
Spuriousness-Aware Meta-Learning for Learning Robust Classifiers
Guangtao Zheng, Wenqian Ye, Aidong Zhang
Spurious correlations are brittle associations between certain attributes of inputs and target variables, such as the correlation between an image background and an object class. D…
MM-SpuBench: Towards Better Understanding of Spurious Biases in Multimodal LLMs
Wenqian Ye, Bohan Liu, Guangtao Zheng +6
Spurious bias, a tendency to exploit spurious correlations between superficial input attributes and prediction targets, has revealed a severe robustness pitfall in classical machin…
What is the Visual Cognition Gap between Humans and Multimodal LLMs?
Xu Cao, Yifan Shen, Bolin Lai +8
Recently, Multimodal Large Language Models (MLLMs) and Vision Language Models (VLMs) have shown great promise in language-guided perceptual tasks such as recognition, segmentation,…
MACP: Efficient Model Adaptation for Cooperative Perception
Yunsheng Ma, Juanwu Lu, Can Cui +4
Vehicle-to-vehicle (V2V) communications have greatly enhanced the perception capabilities of connected and automated vehicles (CAVs) by enabling information sharing to "see through…
CEMFormer: Learning to Predict Driver Intentions from In-Cabin and External Cameras via Spatial-Temporal Transformers
Yunsheng Ma, Wenqian Ye, Xu Cao +4
Driver intention prediction seeks to anticipate drivers' actions by analyzing their behaviors with respect to surrounding traffic environments. Existing approaches primarily focus…
ViTASD: Robust Vision Transformer Baselines for Autism Spectrum Disorder Facial Diagnosis
Xu Cao, Wenqian Ye, Elena Sizikova +4
Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder with very high prevalence around the world. Research progress in the field of ASD facial analysis in pediat…