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 301–350 of 1878 papers

TitleStatusHype
Dual-Level Collaborative Transformer for Image CaptioningCode1
Generalizing from SIMPLE to HARD Visual Reasoning: Can We Mitigate Modality Imbalance in VLMs?Code1
A Good Prompt Is Worth Millions of Parameters: Low-resource Prompt-based Learning for Vision-Language ModelsCode1
EDSL: An Encoder-Decoder Architecture with Symbol-Level Features for Printed Mathematical Expression RecognitionCode1
End-to-End Supermask Pruning: Learning to Prune Image Captioning ModelsCode1
GRIT: Faster and Better Image captioning Transformer Using Dual Visual FeaturesCode1
Hard Non-Monotonic Attention for Character-Level TransductionCode1
Harnessing the Power of Large Vision Language Models for Synthetic Image DetectionCode1
Human-like Controllable Image Captioning with Verb-specific Semantic RolesCode1
IC3: Image Captioning by Committee ConsensusCode1
Image Captioning Evaluation in the Age of Multimodal LLMs: Challenges and Future PerspectivesCode1
Image Captioning In the Transformer AgeCode1
Image Captioning with Sparse Recurrent Neural NetworkCode1
CgT-GAN: CLIP-guided Text GAN for Image CaptioningCode1
A large annotated corpus for learning natural language inferenceCode1
Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer NetworkCode1
In Defense of Grid Features for Visual Question AnsweringCode1
InfMLLM: A Unified Framework for Visual-Language TasksCode1
BRIDGE: Bridging Gaps in Image Captioning Evaluation with Stronger Visual CuesCode1
Do LVLMs Understand Charts? Analyzing and Correcting Factual Errors in Chart CaptioningCode1
ChatEarthNet: A Global-Scale Image-Text Dataset Empowering Vision-Language Geo-Foundation ModelsCode1
Brain Captioning: Decoding human brain activity into images and textCode1
Compact Bidirectional Transformer for Image CaptioningCode1
Language Guided Visual Question Answering: Elevate Your Multimodal Language Model Using Knowledge-Enriched PromptsCode1
Large-Scale Bidirectional Training for Zero-Shot Image CaptioningCode1
Latent Normalizing Flows for Many-to-Many Cross-Domain MappingsCode1
Dual-branch Hybrid Learning Network for Unbiased Scene Graph GenerationCode1
End-to-End Transformer Based Model for Image CaptioningCode1
FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report GenerationCode1
Length-Controllable Image CaptioningCode1
Bottom-Up and Top-Down Attention for Image Captioning and Visual Question AnsweringCode1
Linearly Mapping from Image to Text SpaceCode1
A Picture is Worth More Than 77 Text Tokens: Evaluating CLIP-Style Models on Dense CaptionsCode1
Disentangled Pre-training for Human-Object Interaction DetectionCode1
Bootstrapping Interactive Image-Text Alignment for Remote Sensing Image CaptioningCode1
Boostlet.js: Image processing plugins for the web via JavaScript injectionCode1
DiscoVLA: Discrepancy Reduction in Vision, Language, and Alignment for Parameter-Efficient Video-Text RetrievalCode1
CLIPTrans: Transferring Visual Knowledge with Pre-trained Models for Multimodal Machine TranslationCode1
M3P: Learning Universal Representations via Multitask Multilingual Multimodal Pre-trainingCode1
CNN+CNN: Convolutional Decoders for Image CaptioningCode1
Distinctive Image Captioning: Leveraging Ground Truth Captions in CLIP Guided Reinforcement LearningCode1
Coarse-to-Fine Vision-Language Pre-training with Fusion in the BackboneCode1
Boosting Transferability in Vision-Language Attacks via Diversification along the Intersection Region of Adversarial TrajectoryCode1
Contrastive Vision-Language Alignment Makes Efficient Instruction LearnerCode1
CoCa: Contrastive Captioners are Image-Text Foundation ModelsCode1
MedMax: Mixed-Modal Instruction Tuning for Training Biomedical AssistantsCode1
MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language ModelsCode1
COCO-Stuff: Thing and Stuff Classes in ContextCode1
Mining Fine-Grained Image-Text Alignment for Zero-Shot Captioning via Text-Only TrainingCode1
DiffX: Guide Your Layout to Cross-Modal Generative ModelingCode1
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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