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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 601–650 of 1878 papers

TitleStatusHype
Enhancing image captioning with depth information using a Transformer-based framework—0
OxfordTVG-HIC: Can Machine Make Humorous Captions from Images?—0
Improving Multimodal Datasets with Image Captioning—0
Embedded Heterogeneous Attention Transformer for Cross-lingual Image Captioning—0
Image Captions are Natural Prompts for Text-to-Image ModelsCode1
AIC-AB NET: A Neural Network for Image Captioning with Spatial Attention and Text Attributes—0
mBLIP: Efficient Bootstrapping of Multilingual Vision-LLMsCode0
Reading Radiology Imaging Like The Radiologist—0
Emu: Generative Pretraining in MultimodalityCode3
Linear Alignment of Vision-language Models for Image CaptioningCode1
SVIT: Scaling up Visual Instruction TuningCode3
Fooling Contrastive Language-Image Pre-trained Models with CLIPMasterPrintsCode1
Multimodal Prompt Learning for Product Title Generation with Extremely Limited Labels—0
JourneyDB: A Benchmark for Generative Image UnderstandingCode2
More for Less: Compact Convolutional Transformers Enable Robust Medical Image Classification with Limited Data—0
LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image UnderstandingCode2
Palm: Predicting Actions through Language Models @ Ego4D Long-Term Action Anticipation Challenge 2023Code1
Benchmarking Zero-Shot Recognition with Vision-Language Models: Challenges on Granularity and Specificity—0
Semi-supervised Multimodal Representation Learning through a Global WorkspaceCode0
Shikra: Unleashing Multimodal LLM's Referential Dialogue MagicCode2
What Makes ImageNet Look Unlike LAIONCode1
Self-Supervised Image Captioning with CLIP—0
Kosmos-2: Grounding Multimodal Large Language Models to the WorldCode1
Improving Reference-based Distinctive Image Captioning with Contrastive Rewards—0
Improving Image Captioning Descriptiveness by Ranking and LLM-based Fusion—0
Generation of Radiology Findings in Chest X-Ray by Leveraging Collaborative Knowledge—0
Investigating Prompting Techniques for Zero- and Few-Shot Visual Question AnsweringCode1
LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language ModelsCode2
Image Captioners Are Scalable Vision Learners Too—0
Top-Down Framework for Weakly-supervised Grounded Image CaptioningCode0
Scalable 3D Captioning with Pretrained ModelsCode2
A Survey of Vision-Language Pre-training from the Lens of Multimodal Machine Translation—0
Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewardsCode1
Putting Humans in the Image Captioning Loop—0
Towards Adaptable and Interactive Image Captioning with Data Augmentation and Episodic Memory—0
SciCap+: A Knowledge Augmented Dataset to Study the Challenges of Scientific Figure CaptioningCode0
Composition and Deformance: Measuring Imageability with a Text-to-Image ModelCode0
Cheap-fake Detection with LLM using Prompt Engineering—0
"Let's not Quote out of Context": Unified Vision-Language Pretraining for Context Assisted Image Captioning—0
Understanding and Mitigating Copying in Diffusion ModelsCode1
LMCap: Few-shot Multilingual Image Captioning by Retrieval Augmented Language Model PromptingCode0
VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and DatasetCode2
Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language ModelsCode1
Image Captioning with Multi-Context Synthetic Data—0
Contextual Object Detection with Multimodal Large Language ModelsCode2
FuseCap: Leveraging Large Language Models for Enriched Fused Image CaptionsCode1
FACTUAL: A Benchmark for Faithful and Consistent Textual Scene Graph ParsingCode1
CrossGET: Cross-Guided Ensemble of Tokens for Accelerating Vision-Language TransformersCode1
Green Runner: A tool for efficient model selection from model repositories—0
BiomedGPT: A Generalist Vision-Language Foundation Model for Diverse Biomedical TasksCode2
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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