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 1451–1500 of 1878 papers

TitleStatusHype
Adversarial Semantic Alignment for Improved Image Captions—0
CapSal: Leveraging Captioning to Boost Semantics for Salient Object Detection—0
Look Back and Predict Forward in Image Captioning—0
MSCap: Multi-Style Image Captioning With Unpaired Stylized Text—0
Vision-to-Language Tasks Based on Attributes and Attention Mechanism—0
On Measuring Gender Bias in Translation of Gender-neutral PronounsCode0
A Survey on Biomedical Image CaptioningCode0
SuperCaptioning: Image Captioning Using Two-dimensional Word Embedding—0
Image Captioning based on Deep Learning Methods: A Survey—0
Multimodal Transformer with Multi-View Visual Representation for Image Captioning—0
Harvesting Information from Captions for Weakly Supervised Semantic Segmentation—0
Aligning Visual Regions and Textual Concepts for Semantic-Grounded Image RepresentationsCode0
CutMix: Regularization Strategy to Train Strong Classifiers with Localizable FeaturesCode1
Exact Adversarial Attack to Image Captioning via Structured Output Learning with Latent VariablesCode0
Image Captioning with Clause-Focused Metrics in a Multi-Modal Setting for MarketingCode0
Wasserstein Barycenter Model Ensembling—0
PR Product: A Substitute for Inner Product in Neural NetworksCode0
Knowing When to Stop: Evaluation and Verification of Conformity to Output-size Specifications—0
Pointing Novel Objects in Image Captioning—0
BERTScore: Evaluating Text Generation with BERTCode1
Deep Metric Learning Beyond Binary SupervisionCode0
Learning to Collocate Neural Modules for Image Captioning—0
Self-critical n-step Training for Image Captioning—0
Unrestricted Adversarial Examples via Semantic ManipulationCode0
Good News, Everyone! Context driven entity-aware captioning for news imagesCode0
Describing like humans: on diversity in image captioningCode0
Improved Adversarial Image Captioning—0
AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree SearchCode0
Unpaired Image Captioning via Scene Graph Alignments—0
Boosted Attention: Leveraging Human Attention for Image Captioning—0
Evaluating Sequence-to-Sequence Models for Handwritten Text RecognitionCode0
A Weighted Multi-Criteria Decision Making Approach for Image Captioning—0
Show, Translate and TellCode0
Dense Relational Captioning: Triple-Stream Networks for Relationship-Based CaptioningCode1
Human Attention in Image Captioning: Dataset and AnalysisCode0
Image captioning with weakly-supervised attention penalty—0
COMIC: Towards A Compact Image Captioning Model with AttentionCode0
Wasserstein Barycenter Model EnsemblingCode0
Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded—0
VrR-VG: Refocusing Visually-Relevant Relationships—0
Improving Image Captioning by Leveraging Knowledge Graphs—0
Error-Correcting Neural Sequence Prediction—0
Evaluating Text-to-Image Matching using Binary Image Selection (BISON)—0
Improving Sequence-to-Sequence Learning via Optimal Transport—0
Image Based Review Text Generation with Emotional Guidance—0
Hierarchical LSTMs with Adaptive Attention for Visual Captioning—0
nocaps: novel object captioning at scaleCode0
Generating Diverse and Meaningful CaptionsCode0
Feature Fusion Effects of Tensor Product Representation on (De)Compositional Network for Caption Generation for Images—0
Adversarial Inference for Multi-Sentence Video DescriptionCode0
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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