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

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Showing 1651–1700 of 1878 papers

TitleStatusHype
Imperfect Vision Encoders: Efficient and Robust Tuning for Vision-Language Models—0
Implicit Distortion and Fertility Models for Attention-based Encoder-Decoder NMT Model—0
Importance of Self-Attention for Sentiment Analysis—0
Impressions: Understanding Visual Semiotics and Aesthetic Impact—0
Improved Adversarial Image Captioning—0
Improved Alignment of Modalities in Large Vision Language Models—0
Improved Baselines for Data-efficient Perceptual Augmentation of LLMs—0
Adversarial Semantic Alignment for Improved Image Captions—0
Improved Semantic Parsers For If-Then Statements—0
Improving cognitive diagnostics in pathology: a deep learning approach for augmenting perceptional understanding of histopathology images—0
Improving Cross-modal Alignment with Synthetic Pairs for Text-only Image Captioning—0
Improving Diversity and Reducing Redundancy in Paragraph Captions—0
Improving Generalization of Image Captioning with Unsupervised Prompt Learning—0
Improving Image Captioning by Concept-based Sentence Reranking—0
Improving Image Captioning by Leveraging Knowledge Graphs—0
Improving Image Captioning by Mimicking Human Reformulation Feedback at Inference-time—0
Improving Image Captioning Descriptiveness by Ranking and LLM-based Fusion—0
Improving Image Captioning Evaluation by Considering Inter References Variance—0
Improving Image Captioning via Predicting Structured Concepts—0
Improving Image Captioning with Better Use of Caption—0
Improving Image Captioning with Control Signal of Sentence Quality—0
Improving mitosis detection on histopathology images using large vision-language models—0
Improving Multimodal Datasets with Image Captioning—0
Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring—0
Improving OCR-Based Image Captioning by Incorporating Geometrical Relationship—0
Improving Reference-based Distinctive Image Captioning with Contrastive Rewards—0
Improving Sequence-to-Sequence Learning via Optimal Transport—0
Improving Visual Question Answering by Referring to Generated Paragraph Captions—0
Incorporating Copying Mechanism in Image Captioning for Learning Novel Objects—0
Incorporating Deep Visual Features into Multiobjective based Multi-view Search Results Clustering—0
Incorporating Semantic Attention in Video Description Generation—0
Incorporating Side Information into Recurrent Neural Network Language Models—0
Inductive Visual Localisation: Factorised Training for Superior Generalisation—0
Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework—0
Informative Image Captioning with External Sources of Information—0
Informative Scene Graph Generation via Debiasing—0
Informativity in Image Captions vs. Referring Expressions—0
Input Combination Strategies for Multi-Source Transformer Decoder—0
Inserting Faces inside Captions: Image Captioning with Attention Guided Merging—0
InsightVision: A Comprehensive, Multi-Level Chinese-based Benchmark for Evaluating Implicit Visual Semantics in Large Vision Language Models—0
Instance-aware Remote Sensing Image Captioning with Cross-hierarchy Attention—0
Integrating Image Captioning with Rule-based Entity Masking—0
Integrating Vision and Language Datasets to Measure Word Concreteness—0
Intention Oriented Image Captions with Guiding Objects—0
Interactive Attention AI to translate low light photos to captions for night scene understanding in women safety—0
Interactive Machine Learning for Image Captioning—0
Interpretable Video Captioning via Trajectory Structured Localization—0
Interpretable Visual Question Answering Referring to Outside Knowledge—0
Interpreting Context of Images using Scene Graphs—0
Intra-agent speech permits zero-shot task acquisition—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