57 citations · 125 across the 36 of their papers we have counts for
17 papers · 1 filter
MM-MoralBench: A MultiModal Moral Evaluation Benchmark for Large Vision-Language Models
Bei Yan, Jie Zhang, Zhiyuan Chen +2
The rapid integration of Large Vision-Language Models (LVLMs) into critical domains necessitates comprehensive moral evaluation to ensure their alignment with human values. While e…
Multi-PA: A Multi-perspective Benchmark on Privacy Assessment for Large Vision-Language Models
Jie Zhang, Xiangkui Cao, Zhouyu Han +2
Large Vision-Language Models (LVLMs) exhibit impressive potential across various tasks but also face significant privacy risks, limiting their practical applications. Current resea…
Semantic or Covariate? A Study on the Intractable Case of Out-of-Distribution Detection
Xingming Long, Jie Zhang, Shiguang Shan +1
The primary goal of out-of-distribution (OOD) detection tasks is to identify inputs with semantic shifts, i.e., if samples from novel classes are absent in the in-distribution (ID)…
Confidence Aware Learning for Reliable Face Anti-spoofing
Xingming Long, Jie Zhang, Shiguang Shan
Current Face Anti-spoofing (FAS) models tend to make overly confident predictions even when encountering unfamiliar scenarios or unknown presentation attacks, which leads to seriou…
T2IShield: Defending Against Backdoors on Text-to-Image Diffusion Models
Zhongqi Wang, Jie Zhang, Shiguang Shan +1
While text-to-image diffusion models demonstrate impressive generation capabilities, they also exhibit vulnerability to backdoor attacks, which involve the manipulation of model ou…
Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs
Jie Zhang, Zhongqi Wang, Mengqi Lei +4
Currently many benchmarks have been proposed to evaluate the perception ability of the Large Vision-Language Models (LVLMs). However, most benchmarks conduct questions by selecting…
Measuring the Measurers: Quality Evaluation of Hallucination Benchmarks for Large Vision-Language Models
Bei Yan, Jie Zhang, Zheng Yuan +2
Despite the outstanding performance in multimodal tasks, Large Vision-Language Models (LVLMs) have been plagued by the issue of hallucination, i.e., generating content that is inco…
VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model
Sibo Wang, Xiangkui Cao, Jie Zhang +4
The emergence of Large Vision-Language Models (LVLMs) marks significant strides towards achieving general artificial intelligence. However, these advancements are accompanied by co…
Rethinking the Evaluation of Out-of-Distribution Detection: A Sorites Paradox
Xingming Long, Jie Zhang, Shiguang Shan +1
Most existing out-of-distribution (OOD) detection benchmarks classify samples with novel labels as the OOD data. However, some marginal OOD samples actually have close semantic con…
BIMM: Brain Inspired Masked Modeling for Video Representation Learning
Zhifan Wan, Jie Zhang, Changzhen Li +1
The visual pathway of human brain includes two sub-pathways, ie, the ventral pathway and the dorsal pathway, which focus on object identification and dynamic information modeling,…
Image to Pseudo-Episode: Boosting Few-Shot Segmentation by Unlabeled Data
Jie Zhang, Yuhan Li, Yude Wang +2
Few-shot segmentation (FSS) aims to train a model which can segment the object from novel classes with a few labeled samples. The insufficient generalization ability of models lead…
Anonymization Prompt Learning for Facial Privacy-Preserving Text-to-Image Generation
Liang Shi, Jie Zhang, Shiguang Shan
Text-to-image diffusion models, such as Stable Diffusion, generate highly realistic images from text descriptions. However, the generation of certain content at such high quality r…
Generalized Face Liveness Detection via De-fake Face Generator
Xingming Long, Jie Zhang, Shiguang Shan
Previous Face Anti-spoofing (FAS) methods face the challenge of generalizing to unseen domains, mainly because most existing FAS datasets are relatively small and lack data diversi…
Collaboratively Self-supervised Video Representation Learning for Action Recognition
Jie Zhang, Zhifan Wan, Lanqing Hu +3
Considering the close connection between action recognition and human pose estimation, we design a Collaboratively Self-supervised Video Representation (CSVR) learning framework sp…
Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness
Sibo Wang, Jie Zhang, Zheng Yuan +1
Large-scale pre-trained vision-language models like CLIP have demonstrated impressive performance across various tasks, and exhibit remarkable zero-shot generalization capability,…
FullLoRA: Efficiently Boosting the Robustness of Pretrained Vision Transformers
Zheng Yuan, Jie Zhang, Shiguang Shan +1
In recent years, the Vision Transformer (ViT) model has gradually become mainstream in various computer vision tasks, and the robustness of the model has received increasing attent…
Towards Robust Semantic Segmentation against Patch-based Attack via Attention Refinement
Zheng Yuan, Jie Zhang, Yude Wang +2
The attention mechanism has been proven effective on various visual tasks in recent years. In the semantic segmentation task, the attention mechanism is applied in various methods,…