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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 901–950 of 1878 papers

TitleStatusHype
Semi-Supervised Image Captioning Considering Wasserstein Graph Matching—0
Self-Supervised Image Captioning with CLIP—0
Semi-supervised Text-based Person Search—0
Senti-Attend: Image Captioning using Sentiment and Attention—0
SentiCap: Generating Image Descriptions with Sentiments—0
Sequence-to-Sequence Neural Net Models for Grapheme-to-Phoneme Conversion—0
Sequential Latent Spaces for Modeling the Intention During Diverse Image Captioning—0
Sheffield MultiMT: Using Object Posterior Predictions for Multimodal Machine Translation—0
Shifted Window Fourier Transform And Retention For Image Captioning—0
Show, Interpret and Tell: Entity-aware Contextualised Image Captioning in Wikipedia—0
Show, Recall, and Tell: Image Captioning with Recall Mechanism—0
Show, Tell and Discriminate: Image Captioning by Self-retrieval with Partially Labeled Data—0
Similar Scenes arouse Similar Emotions: Parallel Data Augmentation for Stylized Image Captioning—0
Simple is not Easy: A Simple Strong Baseline for TextVQA and TextCaps—0
Simple Token-Level Confidence Improves Caption Correctness—0
Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition—0
Sketch2Saliency: Learning to Detect Salient Objects from Human Drawings—0
Sketch Me if You Can: Towards Generating Detailed Descriptions of Object Shape by Grounding in Images and Drawings—0
Sketch-to-Text Generation: Toward Contextual, Creative, and Coherent Composition—0
Self-Supervised Open-Ended Classification with Small Visual Language Models—0
Social Media Ready Caption Generation for Brands—0
Softmax Q-Distribution Estimation for Structured Prediction: A Theoretical Interpretation for RAML—0
Sparse Attention Vectors: Generative Multimodal Model Features Are Discriminative Vision-Language Classifiers—0
Sparse Transformer: Concentrated Attention Through Explicit Selection—0
SPASS: Scientific Prominence Active Search System with Deep Image Captioning Network—0
Spatial Attention as an Interface for Image Captioning Models—0
Spatial Language Understanding with Multimodal Graphs using Declarative Learning based Programming—0
Spatial Pyramid Convolutional Neural Network for Social Event Detection in Static Image—0
SRD: Reinforcement-Learned Semantic Perturbation for Backdoor Defense in VLMs—0
Stacked Cross-modal Feature Consolidation Attention Networks for Image Captioning—0
Stacked Latent Attention for Multimodal Reasoning—0
Steering LVLMs via Sparse Autoencoder for Hallucination Mitigation—0
Structural and Functional Decomposition for Personality Image Captioning in a Communication Game—0
Style-Aware Contrastive Learning for Multi-Style Image Captioning—0
StyleM: Stylized Metrics for Image Captioning Built with Contrastive N-grams—0
SubICap: Towards Subword-informed Image Captioning—0
Summarize the Past to Predict the Future: Natural Language Descriptions of Context Boost Multimodal Object Interaction Anticipation—0
SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding—0
SuperOCR: A Conversion from Optical Character Recognition to Image Captioning—0
Surveying the Landscape of Image Captioning Evaluation: A Comprehensive Taxonomy and Novel Ensemble Method—0
Survey of Large Multimodal Model Datasets, Application Categories and Taxonomy—0
Survey of Visual-Semantic Embedding Methods for Zero-Shot Image Retrieval—0
SyCoCa: Symmetrizing Contrastive Captioners with Attentive Masking for Multimodal Alignment—0
Synchronized Audio-Visual Frames with Fractional Positional Encoding for Transformers in Video-to-Text Translation—0
Synocene, Beyond the Anthropocene: De-Anthropocentralising Human-Nature-AI Interaction—0
Synth^2: Boosting Visual-Language Models with Synthetic Captions and Image Embeddings—0
Synthesizer Based Efficient Self-Attention for Vision Tasks—0
TADACap: Time-series Adaptive Domain-Aware Captioning—0
TakeLab: Systems for Measuring Semantic Text Similarity—0
Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded—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