SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 501–550 of 1878 papers

TitleStatusHype
Zero-shot audio captioning with audio-language model guidance and audio context keywordsCode1
InfMLLM: A Unified Framework for Visual-Language TasksCode1
Monkey: Image Resolution and Text Label Are Important Things for Large Multi-modal ModelsCode3
Holistic Evaluation of GPT-4V for Biomedical Imaging—0
How to Bridge the Gap between Modalities: Survey on Multimodal Large Language Model—0
Zero-shot Translation of Attention Patterns in VQA Models to Natural LanguageCode0
DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing UnderstandingCode0
JaSPICE: Automatic Evaluation Metric Using Predicate-Argument Structures for Image Captioning ModelsCode0
GLaMM: Pixel Grounding Large Multimodal ModelCode2
NeuSyRE: Neuro-Symbolic Visual Understanding and Reasoning Framework based on Scene Graph EnrichmentCode1
Sam-Guided Enhanced Fine-Grained Encoding with Mixed Semantic Learning for Medical Image CaptioningCode1
Visual Analytics for Efficient Image Exploration and User-Guided Image Captioning—0
Enhanced Knowledge Injection for Radiology Report Generation—0
What a Whole Slide Image Can Tell? Subtype-guided Masked Transformer for Pathological Image Captioning—0
Language Guided Visual Question Answering: Elevate Your Multimodal Language Model Using Knowledge-Enriched PromptsCode1
Improving Medical Visual Representations via Radiology Report Generation—0
Myriad: Large Multimodal Model by Applying Vision Experts for Industrial Anomaly DetectionCode1
Women Wearing Lipstick: Measuring the Bias Between an Object and Its Related GenderCode0
CropCap: Embedding Visual Cross-Partition Dependency for Image Captioning—0
Impressions: Understanding Visual Semiotics and Aesthetic Impact—0
Apollo: Zero-shot MultiModal Reasoning with Multiple ExpertsCode0
A Picture is Worth a Thousand Words: Principled Recaptioning Improves Image Generation—0
Semantic and Expressive Variation in Image Captions Across Languages—0
Visual Grounding Helps Learn Word Meanings in Low-Data RegimesCode1
CAPIVARA: Cost-Efficient Approach for Improving Multilingual CLIP Performance on Low-Resource LanguagesCode1
RSAdapter: Adapting Multimodal Models for Remote Sensing Visual Question AnsweringCode0
Lost in Translation: When GPT-4V(ision) Can't See Eye to Eye with Text. A Vision-Language-Consistency Analysis of VLLMs and Beyond—0
CLAIR: Evaluating Image Captions with Large Language Models—0
ICU: Conquering Language Barriers in Vision-and-Language Modeling by Dividing the Tasks into Image Captioning and Language UnderstandingCode0
Evaluating the Fairness of Discriminative Foundation Models in Computer VisionCode0
Towards Automatic Satellite Images Captions Generation Using Large Language Models—0
Bounding and Filling: A Fast and Flexible Framework for Image CaptioningCode0
From CLIP to DINO: Visual Encoders Shout in Multi-modal Large Language ModelsCode2
Ziya-Visual: Bilingual Large Vision-Language Model via Multi-Task Instruction Tuning—0
LangNav: Language as a Perceptual Representation for Navigation—0
A Comparative Study of Pre-trained CNNs and GRU-Based Attention for Image Caption Generation—0
Improving mitosis detection on histopathology images using large vision-language models—0
The Solution for the CVPR2023 NICE Image Captioning Challenge—0
ViCor: Bridging Visual Understanding and Commonsense Reasoning with Large Language Models—0
Lightweight In-Context Tuning for Multimodal Unified Models—0
Module-wise Adaptive Distillation for Multimodality Foundation Models—0
IcoCap: Improving Video Captioning by Compounding Images—0
On the Performance of Multimodal Language Models—0
MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsCode2
Language Models as Knowledge Bases for Visual Word Sense DisambiguationCode0
Sieve: Multimodal Dataset Pruning Using Image Captioning ModelsCode1
Self-Supervised Open-Ended Classification with Small Visual Language Models—0
YOLOR-Based Multi-Task LearningCode5
ELIP: Efficient Language-Image Pre-training with Fewer Vision TokensCode0
Targeted Image Data Augmentation Increases Basic Skills Captioning Robustness—0
Show:102550
← PrevPage 11 of 38Next →
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