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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 1751–1800 of 1878 papers

TitleStatusHype
Attend to You: Personalized Image Captioning with Context Sequence Memory NetworksCode0
Neural Extractive Summarization with Side InformationCode0
Deep Reinforcement Learning-based Image Captioning with Embedding Reward—0
Continuous multilinguality with language vectors—0
The BreakingNews Dataset—0
I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation—0
Recurrent Models for Situation Recognition—0
Towards Diverse and Natural Image Descriptions via a Conditional GANCode0
MIML-FCN+: Multi-instance Multi-label Learning via Fully Convolutional Networks with Privileged Information—0
ViP-CNN: Visual Phrase Guided Convolutional Neural Network—0
MAT: A Multimodal Attentive Translator for Image Captioning—0
Deep Network Guided Proof Search—0
Context-aware Captions from Context-agnostic SupervisionCode0
Vision and Language Integration: Moving beyond Objects—0
Re-evaluating Automatic Metrics for Image Captioning—0
Understanding Image and Text Simultaneously: a Dual Vision-Language Machine Comprehension Task—0
An Empirical Study of Language CNN for Image CaptioningCode0
Beyond Holistic Object Recognition: Enriching Image Understanding with Part States—0
Recurrent Image Captioner: Describing Images with Spatial-Invariant Transformation and Attention Filtering—0
Spatial Pyramid Convolutional Neural Network for Social Event Detection in Static Image—0
Text-guided Attention Model for Image CaptioningCode0
Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image CaptioningCode0
Areas of Attention for Image Captioning—0
Guided Open Vocabulary Image Captioning with Constrained Beam SearchCode0
Improved Image Captioning via Policy Gradient optimization of SPIDErCode0
Video Event Detection by Exploiting Word Dependencies from Image Captions—0
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent SpaceCode0
On Human Intellect and Machine Failures: Troubleshooting Integrative Machine Learning Systems—0
Semantic Compositional Networks for Visual CaptioningCode0
Grad-CAM: Why did you say that?Code0
A Hierarchical Approach for Generating Descriptive Image ParagraphsCode0
SCA-CNN: Spatial and Channel-wise Attention in Convolutional Networks for Image CaptioningCode0
A Semi-supervised Framework for Image CaptioningCode0
Semantic Regularisation for Recurrent Image Annotation—0
Learning a Deep Embedding Model for Zero-Shot LearningCode0
Boosting Image Captioning with Attributes—0
Neural Headline Generation on Abstract Meaning Representation—0
Can Active Memory Replace Attention?Code0
Generating captions without looking beyond objects—0
Multimodal Attention for Neural Machine Translation—0
Effect of Data Annotation, Feature Selection and Model Choice on Spatial Description Generation in French—0
Sketch-to-Text Generation: Toward Contextual, Creative, and Coherent Composition—0
Measuring Machine Intelligence Through Visual Question Answering—0
Utilizing Large Scale Vision and Text Datasets for Image Segmentation from Referring Expressions—0
Learning to generalize to new compositions in image understanding—0
phi-LSTM: A Phrase-based Hierarchical LSTM Model for Image Captioning—0
Seeing with Humans: Gaze-Assisted Neural Image Captioning—0
DeepDiary: Automatic Caption Generation for Lifelogging Image StreamsCode0
Cross-Lingual Image Caption Generation—0
Focused Evaluation for Image Description with Binary Forced-Choice Tasks—0
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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