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 801–850 of 1878 papers

TitleStatusHype
Hand1000: Generating Realistic Hands from Text with Only 1,000 Images—0
CLAIR: Evaluating Image Captions with Large Language Models—0
Improving Image Captioning with Better Use of Caption—0
Harvesting Information from Captions for Weakly Supervised Semantic Segmentation—0
Controllable Image Captioning via Prompting—0
Hidden State Guidance: Improving Image Captioning using An Image Conditioned Autoencoder—0
Aligning Attention Distribution to Information Flow for Hallucination Mitigation in Large Vision-Language Models—0
Hiding-in-Plain-Sight (HiPS) Attack on CLIP for Targetted Object Removal from Images—0
Astrea: A MOE-based Visual Understanding Model with Progressive Alignment—0
Hierarchical LSTMs with Adaptive Attention for Visual Captioning—0
Improving Cross-modal Alignment with Synthetic Pairs for Text-only Image Captioning—0
Hierarchical Prototype Learning for Zero-Shot Recognition—0
Exploring External Knowledge for Accurate modeling of Visual and Language Problems—0
Towards Explainable Neural-Symbolic Visual Reasoning—0
Exploring Explicit and Implicit Visual Relationships for Image Captioning—0
HMGIE: Hierarchical and Multi-Grained Inconsistency Evaluation for Vision-Language Data Cleansing—0
CIC: A Framework for Culturally-Aware Image Captioning—0
HorNet: A Hierarchical Offshoot Recurrent Network for Improving Person Re-ID via Image Captioning—0
How Can Objects Help Video-Language Understanding?—0
How Culturally Aware are Vision-Language Models?—0
HOW IMPORTANT ARE NETWORK WEIGHTS? TO WHAT EXTENT DO THEY NEED AN UPDATE?—0
Improving Diversity and Reducing Redundancy in Paragraph Captions—0
Chittron: An Automatic Bangla Image Captioning System—0
Exploring Causes and Mitigation of Hallucinations in Large Vision Language Models—0
How Vision Affects Language: Comparing Masked Self-Attention in Uni-Modal and Multi-Modal Transformer—0
How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey—0
Cheap-fake Detection with LLM using Prompt Engineering—0
Assistive Image Annotation Systems with Deep Learning and Natural Language Capabilities: A Review—0
Can Machines Imitate Humans? Integrative Turing Tests for Vision and Language Demonstrate a Narrowing Gap—0
Hyperparameter Analysis for Image Captioning—0
AdaDARE-gamma: Balancing Stability and Plasticity in Multi-modal LLMs through Efficient Adaptation—0
I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation—0
Improving Generalization of Image Captioning with Unsupervised Prompt Learning—0
Exploring and Distilling Cross-Modal Information for Image Captioning—0
Explore and Tell: Embodied Visual Captioning in 3D Environments—0
A Novel Technique for Evidence based Conditional Inference in Deep Neural Networks via Latent Feature Perturbation—0
CropCap: Embedding Visual Cross-Partition Dependency for Image Captioning—0
IcoCap: Improving Video Captioning by Compounding Images—0
Exploiting Pseudo Image Captions for Multimodal Summarization—0
Cross2StrA: Unpaired Cross-lingual Image Captioning with Cross-lingual Cross-modal Structure-pivoted Alignment—0
Assisting Scene Graph Generation with Self-Supervision—0
IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer—0
Exploiting Image–Text Synergy for Contextual Image Captioning—0
Exploiting Cross-Modal Prediction and Relation Consistency for Semi-Supervised Image Captioning—0
Explainable Image Captioning using CNN- CNN architecture and Hierarchical Attention—0
Image2Text2Image: A Novel Framework for Label-Free Evaluation of Image-to-Text Generation with Text-to-Image Diffusion Models—0
Assessing Image Quality Issues for Real-World Problems—0
Auto-ACD: A Large-scale Dataset for Audio-Language Representation Learning—0
Image as a Foreign Language: BEiT Pretraining for Vision and Vision-Language Tasks—0
Improving cognitive diagnostics in pathology: a deep learning approach for augmenting perceptional understanding of histopathology images—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