343 citations · 460 across the 31 of their papers we have counts for
31 papers
GalleryGPT: Analyzing Paintings with Large Multimodal Models
Yi Bin, Wenhao Shi, Yujuan Ding +5
Artwork analysis is important and fundamental skill for art appreciation, which could enrich personal aesthetic sensibility and facilitate the critical thinking ability. Understand…
Leveraging Weak Cross-Modal Guidance for Coherence Modelling via Iterative Learning
Yi Bin, Junrong Liao, Yujuan Ding +4
Cross-modal coherence modeling is essential for intelligent systems to help them organize and structure information, thereby understanding and creating content of the physical worl…
Alleviating Hallucinations in Large Vision-Language Models through Hallucination-Induced Optimization
Xinyu Lyu, Beitao Chen, Lianli Gao +2
Although Large Visual Language Models (LVLMs) have demonstrated exceptional abilities in understanding multimodal data, they invariably suffer from hallucinations, leading to a dis…
AICL: Action In-Context Learning for Video Diffusion Model
Jianzhi Liu, Junchen Zhu, Lianli Gao +2
The open-domain video generation models are constrained by the scale of the training video datasets, and some less common actions still cannot be generated. Some researchers explor…
Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection
Huafeng Liu, Mengmeng Sheng, Zeren Sun +3
Learning with noisy labels has gained increasing attention because the inevitable imperfect labels in real-world scenarios can substantially hurt the deep model performance. Recent…
Make-A-Storyboard: A General Framework for Storyboard with Disentangled and Merged Control
Sitong Su, Litao Guo, Lianli Gao +2
Story Visualization aims to generate images aligned with story prompts, reflecting the coherence of storybooks through visual consistency among characters and scenes.Whereas curren…
ALF: Adaptive Label Finetuning for Scene Graph Generation
Qishen Chen, Jianzhi Liu, Xinyu Lyu +3
Scene Graph Generation (SGG) endeavors to predict the relationships between subjects and objects in a given image. Nevertheless, the long-tail distribution of relations often leads…
JoReS-Diff: Joint Retinex and Semantic Priors in Diffusion Model for Low-light Image Enhancement
Yuhui Wu, Guoqing Wang, Zhiwen Wang +5
Low-light image enhancement (LLIE) has achieved promising performance by employing conditional diffusion models. Despite the success of some conditional methods, previous methods m…
CUCL: Codebook for Unsupervised Continual Learning
Chen Cheng, Jingkuan Song, Xiaosu Zhu +3
The focus of this study is on Unsupervised Continual Learning (UCL), as it presents an alternative to Supervised Continual Learning which needs high-quality manual labeled data. Th…
SAM Meets UAP: Attacking Segment Anything Model With Universal Adversarial Perturbation
Dongshen Han, Chaoning Zhang, Sheng Zheng +3
As Segment Anything Model (SAM) becomes a popular foundation model in computer vision, its adversarial robustness has become a concern that cannot be ignored. This works investigat…
Part-Aware Transformer for Generalizable Person Re-identification
Hao Ni, Yuke Li, Lianli Gao +2
Domain generalization person re-identification (DG-ReID) aims to train a model on source domains and generalize well on unseen domains. Vision Transformer usually yields better gen…
From Global to Local: Multi-scale Out-of-distribution Detection
Ji Zhang, Lianli Gao, Bingguang Hao +3
Out-of-distribution (OOD) detection aims to detect "unknown" data whose labels have not been seen during the in-distribution (ID) training process. Recent progress in representatio…
Cross-Modal Retrieval: A Systematic Review of Methods and Future Directions
Tianshi Wang, Fengling Li, Lei Zhu +3
With the exponential surge in diverse multi-modal data, traditional uni-modal retrieval methods struggle to meet the needs of users seeking access to data across various modalities…
Informative Scene Graph Generation via Debiasing
Lianli Gao, Xinyu Lyu, Yuyu Guo +5
Scene graph generation aims to detect visual relationship triplets, (subject, predicate, object). Due to biases in data, current models tend to predict common predicates, e.g. "on"…
A Universal Unbiased Method for Classification from Aggregate Observations
Zixi Wei, Lei Feng, Bo Han +4
In conventional supervised classification, true labels are required for individual instances. However, it could be prohibitive to collect the true labels for individual instances,…
Instance-Variant Loss with Gaussian RBF Kernel for 3D Cross-modal Retriveal
Zhitao Liu, Zengyu Liu, Jiwei Wei +4
3D cross-modal retrieval is gaining attention in the multimedia community. Central to this topic is learning a joint embedding space to represent data from different modalities, su…
Caterpillar: A Pure-MLP Architecture with Shifted-Pillars-Concatenation
Jin Sun, Xiaoshuang Shi, Zhiyuan Wang +3
Modeling in Computer Vision has evolved to MLPs. Vision MLPs naturally lack local modeling capability, to which the simplest treatment is combined with convolutional layers. Convol…
Imbalanced Open Set Domain Adaptation via Moving-threshold Estimation and Gradual Alignment
Jinghan Ru, Jun Tian, Zhekai Du +3
Multimedia applications are often associated with cross-domain knowledge transfer, where Unsupervised Domain Adaptation (UDA) can be used to reduce the domain shifts. Open Set Doma…
A Comprehensive Survey on Source-free Domain Adaptation
Zhiqi Yu, Jingjing Li, Zhekai Du +2
Over the past decade, domain adaptation has become a widely studied branch of transfer learning that aims to improve performance on target domains by leveraging knowledge from the…
Semantic Enhanced Knowledge Graph for Large-Scale Zero-Shot Learning
Jiwei Wei, Yang Yang, Zeyu Ma +3
Zero-Shot Learning has been a highlighted research topic in both vision and language areas. Recently, most existing methods adopt structured knowledge information to model explicit…
KE-RCNN: Unifying Knowledge based Reasoning into Part-level Attribute Parsing
Xuanhan Wang, Jingkuan Song, Xiaojia Chen +3
Part-level attribute parsing is a fundamental but challenging task, which requires the region-level visual understanding to provide explainable details of body parts. Most existing…
One-shot Scene Graph Generation
Yuyu Guo, Jingkuan Song, Lianli Gao +1
As a structured representation of the image content, the visual scene graph (visual relationship) acts as a bridge between computer vision and natural language processing. Existing…
Fast Gradient Non-sign Methods
Yaya Cheng, Jingkuan Song, Xiaosu Zhu +3
Adversarial attacks make their success in DNNs, and among them, gradient-based algorithms become one of the mainstreams. Based on the linearity hypothesis, under cons…
Staircase Sign Method for Boosting Adversarial Attacks
Qilong Zhang, Xiaosu Zhu, Jingkuan Song +2
Crafting adversarial examples for the transfer-based attack is challenging and remains a research hot spot. Currently, such attack methods are based on the hypothesis that the subs…