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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 701–750 of 1878 papers

TitleStatusHype
On Speculative Decoding for Multimodal Large Language Models—0
FLoRA: Enhancing Vision-Language Models with Parameter-Efficient Federated LearningCode0
Panoptic Perception: A Novel Task and Fine-grained Dataset for Universal Remote Sensing Image Interpretation—0
Would Deep Generative Models Amplify Bias in Future Models?—0
Jump Self-attention: Capturing High-order Statistics in Transformers—0
VLRM: Vision-Language Models act as Reward Models for Image Captioning—0
Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language ReasoningCode0
LLaMA-Excitor: General Instruction Tuning via Indirect Feature Interaction—0
Text Data-Centric Image Captioning with Interactive Prompts—0
LocCa: Visual Pretraining with Location-aware Captioners—0
Semantic Map-based Generation of Navigation InstructionsCode0
A Review of Multi-Modal Large Language and Vision Models—0
A Survey on Large Language Models from Concept to Implementation—0
Automated Report Generation for Lung Cytological Images Using a CNN Vision Classifier and Multiple-Transformer Text Decoders: Preliminary Study—0
The Solution for the ICCV 2023 1st Scientific Figure Captioning Challenge—0
Visual Hallucination: Definition, Quantification, and Prescriptive Remediations—0
Semi-Supervised Image Captioning Considering Wasserstein Graph Matching—0
Image Captioning in news report scenario—0
Cognitive resilience: Unraveling the proficiency of image-captioning models to interpret masked visual contentCode0
A Multimodal Approach for Cross-Domain Image Retrieval—0
MyVLM: Personalizing VLMs for User-Specific Queries—0
Inserting Faces inside Captions: Image Captioning with Attention Guided Merging—0
Improved Baselines for Data-efficient Perceptual Augmentation of LLMs—0
As Firm As Their Foundations: Can open-sourced foundation models be used to create adversarial examples for downstream tasks?—0
Entity6K: A Large Open-Domain Evaluation Dataset for Real-World Entity Recognition—0
Towards Multimodal In-Context Learning for Vision & Language Models—0
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
Leveraging LLMs for On-the-Fly Instruction Guided Image EditingCode0
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
The Case for Evaluating Multimodal Translation Models on Text Datasets—0
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
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
Exploring the Frontier of Vision-Language Models: A Survey of Current Methodologies and Future Directions—0
IRR: Image Review Ranking Framework for Evaluating Vision-Language Models—0
AICAttack: Adversarial Image Captioning Attack with Attention-Based OptimizationCode0
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models—0
Cobra Effect in Reference-Free Image Captioning MetricsCode0
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
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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