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Image Captioning

Image Captioning is the task of describing the content of an image in words. This task lies at the intersection of computer vision and natural language processing. Most image captioning systems use an encoder-decoder framework, where an input image is encoded into an intermediate representation of the information in the image, and then decoded into a descriptive text sequence. The most popular benchmarks are nocaps and COCO, and models are typically evaluated according to a BLEU or CIDER metric.

( Image credit: Reflective Decoding Network for Image Captioning, ICCV'19)

Papers

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Showing 401–450 of 1878 papers

TitleStatusHype
Entity6K: A Large Open-Domain Evaluation Dataset for Real-World Entity Recognition—0
As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks?—0
Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial TrajectoryCode1
TARN-VIST: Topic Aware Reinforcement Network for Visual Storytelling—0
Few-Shot VQA with Frozen LLMs: A Tale of Two Approaches—0
Does the Performance of Text-to-Image Retrieval Models Generalize Beyond Captions-as-a-Query?Code0
Can We Talk Models Into Seeing the World Differently?Code1
Leveraging LLMs for On-the-Fly Instruction Guided Image EditingCode0
Beyond Text: Frozen Large Language Models in Visual Signal ComprehensionCode2
Synth^2: Boosting Visual-Language Models with Synthetic Captions and Image Embeddings—0
A Comprehensive Survey of 3D Dense Captioning: Localizing and Describing Objects in 3D Scenes—0
Transformer based Multitask Learning for Image Captioning and Object Detection—0
PixArt-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image GenerationCode5
MeaCap: Memory-Augmented Zero-shot Image CaptioningCode2
The Case for Evaluating Multimodal Translation Models on Text Datasets—0
Differentially Private Representation Learning via Image CaptioningCode1
VTG-GPT: Tuning-Free Zero-Shot Video Temporal Grounding with GPTCode2
What Is Missing in Multilingual Visual Reasoning and How to Fix ItCode0
Improving Explicit Spatial Relationships in Text-to-Image Generation through an Automatically Derived DatasetCode0
EAMA : Entity-Aware Multimodal Alignment Based Approach for News Image Captioning—0
Polos: Multimodal Metric Learning from Human Feedback for Image CaptioningCode1
Vision Language Model-based Caption Evaluation Method Leveraging Visual Context Extraction—0
ArcSin: Adaptive ranged cosine Similarity injected noise for Language-Driven Visual Tasks—0
Fine-tuning CLIP Text Encoders with Two-step Paraphrasing—0
Distinctive Image Captioning: Leveraging Ground Truth Captions in CLIP Guided Reinforcement LearningCode1
Exploring the Frontier of Vision-Language Models: A Survey of Current Methodologies and Future Directions—0
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models—0
AICAttack: Adversarial Image Captioning Attack with Attention-Based OptimizationCode0
IRR: Image Review Ranking Framework for Evaluating Vision-Language Models—0
Cobra Effect in Reference-Free Image Captioning MetricsCode0
ChatEarthNet: A Global-Scale Image-Text Dataset Empowering Vision-Language Geo-Foundation ModelsCode1
Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models—0
Captions Are Worth a Thousand Words: Enhancing Product Retrieval with Pretrained Image-to-Text Models—0
Multimodal Learned Sparse Retrieval for Image Suggestion—0
Consistency Model is an Effective Posterior Sample Approximation for Diffusion Inverse Solvers—0
Large Language Models for Captioning and Retrieving Remote Sensing Images—0
Examining Gender and Racial Bias in Large Vision-Language Models Using a Novel Dataset of Parallel ImagesCode0
CIC: A Framework for Culturally-Aware Image Captioning—0
Exploring Visual Culture Awareness in GPT-4V: A Comprehensive Probing—0
GPTs Are Multilingual Annotators for Sequence Generation TasksCode0
Text or Image? What is More Important in Cross-Domain Generalization Capabilities of Hate Meme Detection Models?—0
Image captioning for Brazilian Portuguese using GRIT model—0
Text-Guided Image ClusteringCode1
PICS: Pipeline for Image Captioning and Search—0
SCO-VIST: Social Interaction Commonsense Knowledge-based Visual Storytelling—0
Good at captioning, bad at counting: Benchmarking GPT-4V on Earth observation dataCode0
SciMMIR: Benchmarking Scientific Multi-modal Information RetrievalCode1
Veagle: Advancements in Multimodal Representation LearningCode1
COCO is "ALL'' You Need for Visual Instruction Fine-tuning—0
KTVIC: A Vietnamese Image Captioning Dataset on the Life Domain—0
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All datasetsVizWiz 2020 test-devCOCO Captionsnocaps in-domainnocaps near-domainnocaps out-of-domainnocaps entireCOCO (Common Objects in Context)VizWiz 2020 testnocaps-XD entirenocaps-val-in-domainnocaps-val-overallnocaps-XD in-domain

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IBM Research AICIDEr80.67—Unverified
2CASIA_IVACIDEr79.15—Unverified
3feixiangCIDEr77.31—Unverified
4wocaoCIDEr77.21—Unverified
5lamiwab172CIDEr75.93—Unverified
6RUC_AIM3CIDEr73.52—Unverified
7funasCIDEr73.51—Unverified
8SRC-B_VCLabCIDEr73.47—Unverified
9spartaCIDEr73.41—Unverified
10x-vizCIDEr73.26—Unverified
#ModelMetricClaimedVerifiedStatus
1VALORCIDER152.5—Unverified
2VASTCIDER149—Unverified
3Virtex (ResNet-101)CIDER94—Unverified
4KOSMOS-1 (1.6B) (zero-shot)CIDER84.7—Unverified
5BLIP-FuseCapCLIPScore78.5—Unverified
6mPLUGBLEU-446.5—Unverified
7OFABLEU-444.9—Unverified
8GITBLEU-444.1—Unverified
9BLIP-2 ViT-G OPT 2.7B (zero-shot)BLEU-443.7—Unverified
10BLIP-2 ViT-G OPT 6.7B (zero-shot)BLEU-443.5—Unverified
#ModelMetricClaimedVerifiedStatus
1PaLICIDEr149.1—Unverified
2GIT2, Single ModelCIDEr124.18—Unverified
3GIT, Single ModelCIDEr122.4—Unverified
4PaLICIDEr121.09—Unverified
5CoCa - Google BrainCIDEr117.9—Unverified
6Microsoft Cognitive Services teamCIDEr112.82—Unverified
7Single ModelCIDEr108.98—Unverified
8GRIT (zero-shot, no VL pretraining, no CBS)CIDEr105.9—Unverified
9FudanFVLCIDEr104.9—Unverified
10FudanWYZCIDEr104.25—Unverified
#ModelMetricClaimedVerifiedStatus
1GIT2, Single ModelCIDEr125.51—Unverified
2PaLICIDEr124.35—Unverified
3GIT, Single ModelCIDEr123.92—Unverified
4CoCa - Google BrainCIDEr120.73—Unverified
5Microsoft Cognitive Services teamCIDEr115.54—Unverified
6Single ModelCIDEr110.76—Unverified
7FudanFVLCIDEr109.33—Unverified
8FudanWYZCIDEr108.04—Unverified
9IEDA-LABCIDEr100.15—Unverified
10firetheholeCIDEr99.51—Unverified
#ModelMetricClaimedVerifiedStatus
1PaLICIDEr126.67—Unverified
2GIT2, Single ModelCIDEr122.27—Unverified
3GIT, Single ModelCIDEr122.04—Unverified
4CoCa - Google BrainCIDEr121.69—Unverified
5Microsoft Cognitive Services teamCIDEr110.14—Unverified
6Single ModelCIDEr109.49—Unverified
7FudanFVLCIDEr106.55—Unverified
8FudanWYZCIDEr103.75—Unverified
9HumanCIDEr91.62—Unverified
10firetheholeCIDEr88.54—Unverified