Papers Image Description
“Image Description” 태그가 달린 논문 154편 · 필터 해제
Text-Visual Semantic Constrained AI-Generated Image Quality Assessment
With the rapid advancements in Artificial Intelligence Generated Image (AGI) technology, the accurate assessment of their quality has become an increasingly vital requirement. Prevailing methods typically rely on cross-m…
Image DescriptionImage Quality AssessmentMitigating Hallucinations in Vision-Language Models through Image-Guided Head Suppression
Despite their remarkable progress in multimodal understanding tasks, large vision language models (LVLMs) often suffer from "hallucinations", generating texts misaligned with the visual context. Existing methods aimed at…
HallucinationImage DescriptionQuestion AnsweringVisual Question AnsweringPatho-R1: A Multimodal Reinforcement Learning-Based Pathology Expert Reasoner
Recent advances in vision language models (VLMs) have enabled broad progress in the general medical field. However, pathology still remains a more challenging subdomain, with current pathology specific VLMs exhibiting li…
Cross-Modal RetrievalDiagnosticImage DescriptionMultimodal Reasoning+5Advanced Chest X-Ray Analysis via Transformer-Based Image Descriptors and Cross-Model Attention Mechanism
The examination of chest X-ray images is a crucial component in detecting various thoracic illnesses. This study introduces a new image description generation model that integrates a Vision Transformer (ViT) encoder with…
DecoderImage DescriptionLaMOuR: Leveraging Language Models for Out-of-Distribution Recovery in Reinforcement Learning
Deep Reinforcement Learning (DRL) has demonstrated strong performance in robotic control but remains susceptible to out-of-distribution (OOD) states, often resulting in unreliable actions and task failure. While previous…
Code GenerationDeep Reinforcement LearningImage DescriptionLogical ReasoningVisBias: Measuring Explicit and Implicit Social Biases in Vision Language Models
This research investigates both explicit and implicit social biases exhibited by Vision-Language Models (VLMs). The key distinction between these bias types lies in the level of awareness: explicit bias refers to conscio…
Image DescriptionMultiple-choiceSeedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model
Rapid advancement of diffusion models has catalyzed remarkable progress in the field of image generation. However, prevalent models such as Flux, SD3.5 and Midjourney, still grapple with issues like model bias, limited t…
Image DescriptionImage GenerationInstruction FollowingLarge Language ModelSPIDER: A Comprehensive Multi-Organ Supervised Pathology Dataset and Baseline Models
Advancing AI in computational pathology requires large, high-quality, and diverse datasets, yet existing public datasets are often limited in organ diversity, class coverage, or annotation quality. To bridge this gap, we…
Image DescriptionBoli: A dataset for understanding stuttering experience and analyzing stuttered speech
There is a growing need for diverse, high-quality stuttered speech data, particularly in the context of Indian languages. This paper introduces Project Boli, a multi-lingual stuttered speech dataset designed to advance s…
Image DescriptionIDEA: Image Description Enhanced CLIP-Adapter
CLIP (Contrastive Language-Image Pre-training) has attained great success in pattern recognition and computer vision. Transferring CLIP to downstream tasks (e.g. zero- or few-shot classification) is a hot topic in multim…
Few-Shot Image Classificationimage-classificationImage ClassificationImage Description+1Exploring the Use of Contrastive Language-Image Pre-Training for Human Posture Classification: Insights from Yoga Pose Analysis
Accurate human posture classification in images and videos is crucial for automated applications across various fields, including work safety, physical rehabilitation, sports training, or daily assisted living. Recently,…
Image DescriptionTransfer LearningA Preliminary Survey of Semantic Descriptive Model for Images
Considering the lack of a unified framework for image description and deep cultural analysis at the subject level in the field of Ancient Chinese Paintings (ACP), this study utilized the Beijing Palace Museum's ACP colle…
DescriptiveImage DescriptionSurveyTerm ExtractionRRHF-V: Ranking Responses to Mitigate Hallucinations in Multimodal Large Language Models with Human Feedback
Multimodal large language models (MLLMs) demonstrate strong capabilities in multimodal understanding, reasoning, and interaction but still face the fundamental limitation of hallucinations, where they generate erroneous …
HallucinationImage ComprehensionImage DescriptionPersonalizing Multimodal Large Language Models for Image Captioning: An Experimental Analysis
The task of image captioning demands an algorithm to generate natural language descriptions of visual inputs. Recent advancements have seen a convergence between image captioning research and the development of Large Lan…
Image CaptioningImage DescriptionPrompt LearningTypeScore: A Text Fidelity Metric for Text-to-Image Generative Models
Evaluating text-to-image generative models remains a challenge, despite the remarkable progress being made in their overall performances. While existing metrics like CLIPScore work for coarse evaluations, they lack the s…
Image DescriptionImage GenerationInstruction FollowingText GenerationMiCEval: Unveiling Multimodal Chain of Thought's Quality via Image Description and Reasoning Steps
Multimodal Chain of Thought (MCoT) is a popular prompting strategy for improving the performance of multimodal large language models (MLLMs) across a range of complex reasoning tasks. Despite its popularity, there is a n…
Image DescriptionInformativenessDifficult Task Yes but Simple Task No: Unveiling the Laziness in Multimodal LLMs
Multimodal Large Language Models (MLLMs) demonstrate a strong understanding of the real world and can even handle complex tasks. However, they still fail on some straightforward visual question-answering (VQA) problems. …
Image DescriptionMultiple-choiceQuestion AnsweringVisual Question Answering+1Image Textualization: An Automatic Framework for Creating Accurate and Detailed Image Descriptions
Image description datasets play a crucial role in the advancement of various applications such as image understanding, text-to-image generation, and text-image retrieval. Currently, image description datasets primarily o…
HallucinationImage DescriptionImage GenerationImage Retrieval+2Language Augmentation in CLIP for Improved Anatomy Detection on Multi-modal Medical Images
Vision-language models have emerged as a powerful tool for previously challenging multi-modal classification problem in the medical domain. This development has led to the exploration of automated image description gener…
AnatomyImage DescriptionMulti-modal ClassificationWIDIn: Wording Image for Domain-Invariant Representation in Single-Source Domain Generalization
Language has been useful in extending the vision encoder to data from diverse distributions without empirical discovery in training domains. However, as the image description is mostly at coarse-grained level and ignores…
Domain GeneralizationImage DescriptionSingle-Source Domain Generalization