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 551–600 of 1878 papers

TitleStatusHype
BLIP-Adapter: Parameter-Efficient Transfer Learning for Mobile Screenshot CaptioningCode0
Aligning Large Multimodal Models with Factually Augmented RLHF—0
FaceGemma: Enhancing Image Captioning with Facial Attributes for Portrait Images—0
iPIC-XAI: Improving PIC-XAI for Enhanced Image Captioning ExplanationCode0
Contextual Emotion Estimation from Image Captions—0
Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal AnalysisCode0
Auto-ACD: A Large-scale Dataset for Audio-Language Representation Learning—0
Beyond Generation: Harnessing Text to Image Models for Object Detection and SegmentationCode1
Prefix-diffusion: A Lightweight Diffusion Model for Diverse Image Captioning—0
Towards Better Multi-modal Keyphrase Generation via Visual Entity Enhancement and Multi-granularity Image Noise FilteringCode0
Physically Grounded Vision-Language Models for Robotic Manipulation—0
NICE: CVPR 2023 Challenge on Zero-shot Image Captioning—0
Exchanging-based Multimodal Fusion with TransformerCode1
RSDiff: Remote Sensing Image Generation from Text Using Diffusion Model—0
Towards Addressing the Misalignment of Object Proposal Evaluation for Vision-Language Tasks via Semantic GroundingCode0
Finding-Aware Anatomical Tokens for Chest X-Ray Automated Reporting—0
Can Prompt Learning Benefit Radiology Report Generation?—0
CLIPTrans: Transferring Visual Knowledge with Pre-trained Models for Multimodal Machine TranslationCode1
Towards Real Time Egocentric Segment Captioning for The Blind and Visually Impaired in RGB-D Theatre Images—0
MultiCapCLIP: Auto-Encoding Prompts for Zero-Shot Multilingual Visual CaptioningCode1
VIGC: Visual Instruction Generation and CorrectionCode1
Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and BeyondCode5
DLIP: Distilling Language-Image Pre-training—0
CgT-GAN: CLIP-guided Text GAN for Image CaptioningCode1
With a Little Help from your own Past: Prototypical Memory Networks for Image CaptioningCode1
Explore and Tell: Embodied Visual Captioning in 3D Environments—0
Generic Attention-model Explainability by Weighted Relevance Accumulation—0
VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity ControlCode1
Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme DetectionCode1
Visually-Aware Context Modeling for News Image CaptioningCode0
GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and TextCode1
UniBrain: Unify Image Reconstruction and Captioning All in One Diffusion Model from Human Brain Activity—0
Diffusion Based Augmentation for Captioning and Retrieval in Cultural HeritageCode0
Informative Scene Graph Generation via Debiasing—0
IIHT: Medical Report Generation with Image-to-Indicator Hierarchical Transformer—0
Asynchronous Evolution of Deep Neural Network Architectures—0
Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative InstructionsCode2
Building Safe and Reliable AI systems for Safety Critical Tasks with Vision-Language Processing—0
A Comprehensive Analysis of Real-World Image Captioning and Scene Identification—0
Improving Generalization of Image Captioning with Unsupervised Prompt Learning—0
Multimodal Neurons in Pretrained Text-Only Transformers—0
Beyond Generic: Enhancing Image Captioning with Real-World Knowledge using Vision-Language Pre-Training ModelCode1
TS-RGBD Dataset: a Novel Dataset for Theatre Scenes Description for People with Visual ImpairmentsCode0
ADS-Cap: A Framework for Accurate and Diverse Stylized Captioning with Unpaired Stylistic CorporaCode0
Guiding Image Captioning Models Toward More Specific Captions—0
Transferable Decoding with Visual Entities for Zero-Shot Image CaptioningCode1
Visual Captioning at Will: Describing Images and Videos Guided by a Few Stylized Sentences—0
RSGPT: A Remote Sensing Vision Language Model and BenchmarkCode1
Exploring Annotation-free Image Captioning with Retrieval-augmented Pseudo Sentence GenerationCode0
Causal reasoning in typical computer vision tasks—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