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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 1601–1650 of 1878 papers

TitleStatusHype
GroupCap: Group-Based Image Captioning With Structured Relevance and Diversity Constraints—0
Categorizing Concepts With Basic Level for Vision-to-Language—0
Interpretable Video Captioning via Trajectory Structured Localization—0
Exploring the Functional and Geometric Bias of Spatial Relations Using Neural Language Models—0
Telling Stories with Soundtracks: An Empirical Analysis of Music in Film—0
Generative Bridging Network for Neural Sequence Prediction—0
Generating Image Captions in Arabic using Root-Word Based Recurrent Neural Networks and Deep Neural Networks—0
Visually Guided Spatial Relation Extraction from Text—0
Learning Word Embeddings for Low-Resource Languages by PU Learning—0
Dialog Generation Using Multi-Turn Reasoning Neural Networks—0
How Time Matters: Learning Time-Decay Attention for Contextual Spoken Language Understanding in DialoguesCode0
Fast, Diverse and Accurate Image Captioning Guided By Part-of-Speech—0
Neural Joking Machine : Humorous image captioning—0
Grow and Prune Compact, Fast, and Accurate LSTMs—0
CNN+CNN: Convolutional Decoders for Image CaptioningCode1
Joint Image Captioning and Question Answering—0
Turbo Learning for Captionbot and Drawingbot—0
Neural Architecture Search using Deep Neural Networks and Monte Carlo Tree SearchCode1
SemStyle: Learning to Generate Stylised Image Captions using Unaligned TextCode0
Improving Image Captioning with Conditional Generative Adversarial NetsCode0
Defoiling Foiled Image CaptionsCode0
Token-level and sequence-level loss smoothing for RNN language modelsCode0
Image CaptioningCode0
A vision-grounded dataset for predicting typical locations for verbs—0
Incorporating Semantic Attention in Video Description Generation—0
Edit me: A Corpus and a Framework for Understanding Natural Language Image Editing—0
Annotating Modality Expressions and Event Factuality for a Japanese Chess Commentary Corpus—0
Augmenting Image Question Answering Dataset by Exploiting Image Captions—0
Visual Choice of Plausible Alternatives: An Evaluation of Image-based Commonsense Causal ReasoningCode0
Neural Caption Generation for News Images—0
Adversarial Semantic Alignment for Improved Image Captions—0
No Metrics Are Perfect: Adversarial Reward Learning for Visual StorytellingCode0
Object Counts! Bringing Explicit Detections Back into Image Captioning—0
Entity-aware Image Caption Generation—0
Quantifying the visual concreteness of words and topics in multimodal datasetsCode0
Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style TransferCode0
Pragmatically Informative Image Captioning with Character-Level Inference—0
Decoupled Novel Object CaptionerCode0
Discovery and usage of joint attention in images—0
Natural Language Statistical Features of LSTM-generated Texts—0
Finding beans in burgers: Deep semantic-visual embedding with localizationCode0
Learning to Guide Decoding for Image Captioning—0
Guide Me: Interacting with Deep Networks—0
Regularizing RNNs for Caption Generation by Reconstructing The Past with The PresentCode0
Two can play this Game: Visual Dialog with Discriminative Question Generation and Answering—0
Neural Baby TalkCode0
Women also Snowboard: Overcoming Bias in Captioning ModelsCode1
Show, Tell and Discriminate: Image Captioning by Self-retrieval with Partially Labeled Data—0
Unpaired Image Captioning by Language Pivoting—0
Discriminability objective for training descriptive captionsCode0
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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