Feng, Y.S.[Yan-Song],
Lapata, M.,
Automatic Caption Generation for News Images,
PAMI(35), No. 4, April 2013, pp. 797-812.
IEEE DOI
1303
Use existing captions and tags, expand to similar images.
BibRef
Nakayama, H.[Hideki],
Harada, T.[Tatsuya],
Kuniyoshi, Y.[Yasuo],
Dense Sampling Low-Level Statistics of Local Features,
IEICE(E93-D), No. 7, July 2010, pp. 1727-1736.
WWW Link.
1008
BibRef
Earlier:
CIVR09(Article No 17).
DOI Link
0907
BibRef
And:
Global Gaussian approach for scene categorization using information
geometry,
CVPR10(2336-2343).
IEEE DOI
1006
BibRef
Earlier:
AI Goggles: Real-time Description and Retrieval in the Real World with
Online Learning,
CRV09(184-191).
IEEE DOI
0905
local features.
Scalability of matching for large-scale indexing.
Boost global features with sampled statistics of local features.
BibRef
Ushiku, Y.[Yoshitaka],
Yamaguchi, M.[Masataka],
Mukuta, Y.[Yusuke],
Harada, T.[Tatsuya],
Common Subspace for Model and Similarity:
Phrase Learning for Caption Generation from Images,
ICCV15(2668-2676)
IEEE DOI
1602
Feature extraction
BibRef
Jin, J.[Jiren],
Nakayama, H.[Hideki],
Annotation order matters:
Recurrent Image Annotator for arbitrary length image tagging,
ICPR16(2452-2457)
IEEE DOI
1705
Correlation, Feature extraction, Indexes, Predictive models,
Recurrent neural networks, Training
BibRef
Harada, T.[Tatsuya],
Nakayama, H.[Hideki],
Kuniyoshi, Y.[Yasuo],
Improving Local Descriptors by Embedding Global and Local Spatial
Information,
ECCV10(IV: 736-749).
Springer DOI
1009
BibRef
Earlier: A2, A1, A3:
Evaluation of dimensionality reduction methods for image
auto-annotation,
BMVC10(xx-yy).
HTML Version.
1009
BibRef
Verma, Y.[Yashaswi],
Jawahar, C.V.,
A support vector approach for cross-modal search of images and texts,
CVIU(154), No. 1, 2017, pp. 48-63.
Elsevier DOI
1612
Image search
BibRef
Xue, J.F.[Jian-Fei],
Eguchi, K.[Koji],
Video Data Modeling Using Sequential Correspondence Hierarchical
Dirichlet Processes,
IEICE(E100-D), No. 1, January 2017, pp. 33-41.
WWW Link.
1701
multimodal data such as the mixture of visual words and speech words
extracted from video files
BibRef
Tariq, A.[Amara],
Foroosh, H.[Hassan],
A Context-Driven Extractive Framework for Generating Realistic Image
Descriptions,
IP(26), No. 2, February 2017, pp. 619-632.
IEEE DOI
1702
image annotation
BibRef
Vinyals, O.[Oriol],
Toshev, A.[Alexander],
Bengio, S.[Samy],
Erhan, D.[Dumitru],
Show and Tell: Lessons Learned from the 2015 MSCOCO Image Captioning
Challenge,
PAMI(39), No. 4, April 2017, pp. 652-663.
IEEE DOI
1703
BibRef
Earlier:
Show and tell: A neural image caption generator,
CVPR15(3156-3164)
IEEE DOI
1510
Computational modeling
BibRef
Gao, L.,
Guo, Z.,
Zhang, H.,
Xu, X.,
Shen, H.T.,
Video Captioning With Attention-Based LSTM and Semantic Consistency,
MultMed(19), No. 9, September 2017, pp. 2045-2055.
IEEE DOI
1708
Computational modeling, Correlation, Feature extraction,
Neural networks, Semantics, Two dimensional displays,
Visualization, Attention mechanism, embedding,
long short-term memory (LSTM), video, captioning
BibRef
Hu, M.,
Yang, Y.,
Shen, F.,
Zhang, L.,
Shen, H.T.,
Li, X.,
Robust Web Image Annotation via Exploring Multi-Facet and Structural
Knowledge,
IP(26), No. 10, October 2017, pp. 4871-4884.
IEEE DOI
1708
image annotation, image retrieval, iterative methods,
learning (artificial intelligence), multimedia systems,
optimisation, pattern classification, RMSL,
data structural information,
digital technologies,
image semantic indexing, image semantic retrieval,
robust multiview semi-supervised learning, visual features,
Manifolds, Multimedia communication, Semantics,
Semisupervised learning, Supervised learning, Image annotation,
l2, p-norm, multi-view learning, semi-supervised learning
BibRef
Wang, J.Y.[Jing-Ya],
Zhu, X.T.[Xia-Tian],
Gong, S.G.[Shao-Gang],
Discovering visual concept structure with sparse and incomplete tags,
AI(250), No. 1, 2017, pp. 16-36.
Elsevier DOI
1708
Automatically discovering the semantic structure of tagged visual data
(e.g. web videos and images).
BibRef
Kilickaya, M.[Mert],
Akkus, B.K.[Burak Kerim],
Cakici, R.[Ruket],
Erdem, A.[Aykut],
Erdem, E.[Erkut],
Ikizler-Cinbis, N.[Nazli],
Data-driven image captioning via salient region discovery,
IET-CV(11), No. 6, September 2017, pp. 398-406.
DOI Link
1709
BibRef
Fu, K.[Kun],
Jin, J.Q.[Jun-Qi],
Cui, R.P.[Run-Peng],
Sha, F.[Fei],
Zhang, C.S.[Chang-Shui],
Aligning Where to See and What to Tell: Image Captioning with
Region-Based Attention and Scene-Specific Contexts,
PAMI(39), No. 12, December 2017, pp. 2321-2334.
IEEE DOI
1711
Adaptation models, Computational modeling, Context modeling,
Data mining, Feature extraction, Image classification,
Visualization, Image captioning, LSTM,
visual attention.
BibRef
Liu, A.A.[An-An],
Xu, N.[Ning],
Wong, Y.[Yongkang],
Li, J.[Junnan],
Su, Y.T.[Yu-Ting],
Kankanhalli, M.[Mohan],
Hierarchical & multimodal video captioning: Discovering and
transferring multimodal knowledge for vision to language,
CVIU(163), No. 1, 2017, pp. 113-125.
Elsevier DOI
1712
Video to text
BibRef
Nian, F.D.[Fu-Dong],
Li, T.[Teng],
Wang, Y.[Yan],
Wu, X.Y.[Xin-Yu],
Ni, B.B.[Bing-Bing],
Xu, C.S.[Chang-Sheng],
Learning explicit video attributes from mid-level representation for
video captioning,
CVIU(163), No. 1, 2017, pp. 126-138.
Elsevier DOI
1712
Mid-level video representation
BibRef
He, X.D.[Xiao-Dong],
Deng, L.[Li],
Deep Learning for Image-to-Text Generation: A Technical Overview,
SPMag(34), No. 6, November 2017, pp. 109-116.
IEEE DOI
1712
BibRef
And:
Errata:
SPMag(35), No. 1, January 2018, pp. 178.
IEEE DOI Artificial intelligence, Computer vision, Image classification,
Natural language processing, Pediatrics, Semantics, Training data,
Visualization
BibRef
Li, L.H.[Ling-Hui],
Tang, S.[Sheng],
Zhang, Y.D.[Yong-Dong],
Deng, L.X.[Li-Xi],
Tian, Q.[Qi],
GLA: Global-Local Attention for Image Description,
MultMed(20), No. 3, March 2018, pp. 726-737.
IEEE DOI
1802
Computational modeling, Decoding, Feature extraction,
Image recognition, Natural language processing,
recurrent neural network
BibRef
Guan, J.N.[Jin-Ning],
Wang, E.[Eric],
Repeated review based image captioning for image evidence review,
SP:IC(63), 2018, pp. 141-148.
Elsevier DOI
1804
Repeated review, Image captioning, Encoder-decoder, Multimodal layer
BibRef
Lu, X.,
Wang, B.,
Zheng, X.,
Li, X.,
Exploring Models and Data for Remote Sensing Image Caption Generation,
GeoRS(56), No. 4, April 2018, pp. 2183-2195.
IEEE DOI
1804
Computer vision, Feature extraction, Image representation,
Recurrent neural networks, Remote sensing, Semantics,
semantic understanding
BibRef
Cheng, Q.[Qimin],
Zhang, Q.[Qian],
Fu, P.[Peng],
Tu, C.H.[Cong-Huan],
Li, S.[Sen],
A survey and analysis on automatic image annotation,
PR(79), 2018, pp. 242-259.
Elsevier DOI
1804
Automatic image annotation, Generative model,
Nearest-neighbor model, Discriminative model, Tag-completion, Deep learning
BibRef
Ben Rejeb, I.[Imen],
Ouni, S.[Sonia],
Barhoumi, W.[Walid],
Zagrouba, E.[Ezzeddine],
Fuzzy VA-Files for multi-label image annotation based on visual content
of regions,
SIViP(12), No. 5, July 2018, pp. 877-884.
Springer DOI
1806
Vector Approximation Files.
BibRef
Helmy, T.[Tarek],
A Generic Framework for Semantic Annotation of Images,
IJIG(18), No. 3, July 2018, pp. Article 1850013.
DOI Link
1807
BibRef
Wu, C.L.[Chun-Lei],
Wei, Y.[Yiwei],
Chu, X.L.[Xiao-Liang],
Su, F.[Fei],
Wang, L.[Leiquan],
Modeling visual and word-conditional semantic attention for image
captioning,
SP:IC(67), 2018, pp. 100-107.
Elsevier DOI
1808
Image captioning, Word-conditional semantic attention,
Visual attention, Attention variation
BibRef
Zhang, Z.,
Wu, Q.,
Wang, Y.,
Chen, F.,
Fine-Grained and Semantic-Guided Visual Attention for Image
Captioning,
WACV18(1709-1717)
IEEE DOI
1806
feedforward neural nets, image representation, image resolution,
image segmentation, convolutional neural network,
Visualization
BibRef
Yao, L.[Li],
Ballas, N.[Nicolas],
Cho, K.[Kyunghyun],
Smith, J.[John],
Bengio, Y.[Yoshua],
Oracle Performance for Visual Captioning,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
Shin, A.[Andrew],
Ushiku, Y.[Yoshitaka],
Harada, T.[Tatsuya],
Image Captioning with Sentiment Terms via Weakly-Supervised Sentiment
Dataset,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
Khatchatoorian, A.G.,
Jamzad, M.,
Post Rectifying Methods to Improve the Accuracy of Image Annotation,
DICTA17(1-7)
IEEE DOI
1804
feature extraction, image annotation, image classification,
image retrieval, matrix algebra, Class-tag relation matrix,
Time division multiplexing
BibRef
Dong, H.[Hao],
Zhang, J.Q.[Jing-Qing],
McIlwraith, D.[Douglas],
Guo, Y.[Yike],
I2T2I: Learning text to image synthesis with textual data
augmentation,
ICIP17(2015-2019)
IEEE DOI
1803
Birds, Generators, Image generation,
Recurrent neural networks, Shape, Training, Deep learning, GAN, Image Synthesis
BibRef
Pellegrin, L.[Luis],
Escalante, H.J.[Hugo Jair],
Montes-y-Gómez, M.[Manuel],
Villegas, M.[Mauricio],
González, F.A.[Fabio A.],
A Flexible Framework for the Evaluation of Unsupervised Image
Annotation,
CIARP17(508-516).
Springer DOI
1802
BibRef
Jia, Y.H.[Yu-Hua],
Bai, L.[Liang],
Wang, P.[Peng],
Guo, J.L.[Jin-Lin],
Xie, Y.X.[Yu-Xiang],
Deep Convolutional Neural Network for Correlating Images and Sentences,
MMMod18(I:154-165).
Springer DOI
1802
BibRef
Liu, J.Y.[Jing-Yu],
Wang, L.[Liang],
Yang, M.H.[Ming-Hsuan],
Referring Expression Generation and Comprehension via Attributes,
ICCV17(4866-4874)
IEEE DOI
1802
Language Descriptions for objects.
learning (artificial intelligence), object detection, RefCOCO,
RefCOCO+, RefCOCOg, attribute learning model, common space model,
Visualization
BibRef
Dai, B.,
Fidler, S.,
Urtasun, R.,
Lin, D.,
Towards Diverse and Natural Image Descriptions via a Conditional GAN,
ICCV17(2989-2998)
IEEE DOI
1802
image retrieval, image sequences, inference mechanisms,
learning (artificial intelligence),
Visualization
BibRef
Niu, Z.X.[Zhen-Xing],
Zhou, M.[Mo],
Wang, L.[Le],
Gao, X.[Xinbo],
Hua, G.[Gang],
Hierarchical Multimodal LSTM for Dense Visual-Semantic Embedding,
ICCV17(1899-1907)
IEEE DOI
1802
map sentences and images.
document image processing, image representation,
recurrent neural nets, HM-LSTM, Hierarchical Multimodal LSTM,
Recurrent neural networks
BibRef
Liang, X.,
Hu, Z.,
Zhang, H.,
Gan, C.,
Xing, E.P.,
Recurrent Topic-Transition GAN for Visual Paragraph Generation,
ICCV17(3382-3391)
IEEE DOI
1802
document image processing, inference mechanisms, natural scenes,
recurrent neural nets, text analysis, RTT-GAN,
Visualization
BibRef
Shetty, R.,
Rohrbach, M.,
Hendricks, L.A.,
Fritz, M.,
Schiele, B.,
Speaking the Same Language:
Matching Machine to Human Captions by Adversarial Training,
ICCV17(4155-4164)
IEEE DOI
1802
image matching, learning (artificial intelligence),
sampling methods, vocabulary, adversarial training,
Visualization
BibRef
Liu, S.,
Zhu, Z.,
Ye, N.,
Guadarrama, S.,
Murphy, K.,
Improved Image Captioning via Policy Gradient optimization of SPIDEr,
ICCV17(873-881)
IEEE DOI
1802
Maximum likelihood estimation, Measurement, Mixers, Robustness,
SPICE, Training
BibRef
Gu, J.,
Wang, G.,
Cai, J.,
Chen, T.,
An Empirical Study of Language CNN for Image Captioning,
ICCV17(1231-1240)
IEEE DOI
1802
computer vision, convolution, learning (artificial intelligence),
natural language processing, recurrent neural nets,
Recurrent neural networks
BibRef
Pedersoli, M.,
Lucas, T.,
Schmid, C.,
Verbeek, J.,
Areas of Attention for Image Captioning,
ICCV17(1251-1259)
IEEE DOI
1802
image segmentation, inference mechanisms,
natural language processing, object detection,
Visualization
BibRef
Li, Y.,
Ouyang, W.,
Zhou, B.,
Wang, K.,
Wang, X.,
Scene Graph Generation from Objects, Phrases and Region Captions,
ICCV17(1270-1279)
IEEE DOI
1802
graph theory, image classification, image representation,
neural nets, object detection,
Visualization
BibRef
Zhang, Z.,
Wu, J.J.,
Li, Q.,
Huang, Z.,
Traer, J.,
McDermott, J.H.,
Tenenbaum, J.B.,
Freeman, W.T.,
Generative Modeling of Audible Shapes for Object Perception,
ICCV17(1260-1269)
IEEE DOI
1802
audio recording, audio signal processing, audio-visual systems,
feature extraction, inference mechanisms, interactive systems,
Visualization
BibRef
Wu, J.J.[Jia-Jun],
Lim, J.[Joseph],
Zhang, H.Y.[Hong-Yi],
Tenenbaum, J.B.[Joshua B.],
Freeman, W.T.[William T.],
Physics 101: Learning Physical Object Properties from Unlabeled Videos,
BMVC16(xx-yy).
HTML Version.
1805
BibRef
Tavakoliy, H.R.,
Shetty, R.,
Borji, A.,
Laaksonen, J.,
Paying Attention to Descriptions Generated by Image Captioning Models,
ICCV17(2506-2515)
IEEE DOI
1802
feature extraction, image processing, human descriptions,
human-written descriptions, image captioning model,
Visualization
BibRef
Chen, T.H.,
Liao, Y.H.,
Chuang, C.Y.,
Hsu, W.T.,
Fu, J.,
Sun, M.,
Show, Adapt and Tell:
Adversarial Training of Cross-Domain Image Captioner,
ICCV17(521-530)
IEEE DOI
1802
image processing, inference mechanisms, text analysis, MSCOCO,
adversarial training procedure, captioner act, critic networks,
Training data
BibRef
Tripathi, A.[Anurag],
Gupta, A.[Abhinav],
Chaudhary, S.[Santanu],
Lall, B.[Brejesh],
Image Annotation Using Latent Components and Transmedia Association,
PReMI17(493-500).
Springer DOI
1711
BibRef
Pini, S.[Stefano],
Cornia, M.[Marcella],
Baraldi, L.[Lorenzo],
Cucchiara, R.[Rita],
Towards Video Captioning with Naming:
A Novel Dataset and a Multi-modal Approach,
CIAP17(II:384-395).
Springer DOI
1711
BibRef
Wu, B.Y.[Bao-Yuan],
Jia, F.[Fan],
Liu, W.[Wei],
Ghanem, B.[Bernard],
Diverse Image Annotation,
CVPR17(6194-6202)
IEEE DOI
1711
Correlation, Feature extraction, Measurement, Redundancy, Semantics
BibRef
Krause, J.[Jonathan],
Johnson, J.[Justin],
Krishna, R.[Ranjay],
Fei-Fei, L.[Li],
A Hierarchical Approach for Generating Descriptive Image Paragraphs,
CVPR17(3337-3345)
IEEE DOI
1711
Feature extraction, Natural languages, Pragmatics,
Recurrent neural networks, Speech, Visualization
BibRef
Vedantam, R.,
Bengio, S.,
Murphy, K.,
Parikh, D.,
Chechik, G.,
Context-Aware Captions from Context-Agnostic Supervision,
CVPR17(1070-1079)
IEEE DOI
1711
Birds, Cats, Cognition, Context modeling, Pragmatics, Training
BibRef
Gan, Z.,
Gan, C.,
He, X.,
Pu, Y.,
Tran, K.,
Gao, J.,
Carin, L.,
Deng, L.,
Semantic Compositional Networks for Visual Captioning,
CVPR17(1141-1150)
IEEE DOI
1711
Feature extraction, Mouth, Pediatrics, Semantics, Tensile stress,
Training, Visualization
BibRef
Ren, Z.,
Wang, X.,
Zhang, N.,
Lv, X.,
Li, L.J.,
Deep Reinforcement Learning-Based Image Captioning with Embedding
Reward,
CVPR17(1151-1159)
IEEE DOI
1711
Decision making, Learning (artificial intelligence), Measurement,
Neural networks, Training, Visualization
BibRef
Rennie, S.J.,
Marcheret, E.,
Mroueh, Y.,
Ross, J.,
Goel, V.,
Self-Critical Sequence Training for Image Captioning,
CVPR17(1179-1195)
IEEE DOI
1711
Inference algorithms, Learning (artificial intelligence),
Logic gates, Measurement, Predictive models, Training
BibRef
Yang, L.,
Tang, K.,
Yang, J.,
Li, L.J.,
Dense Captioning with Joint Inference and Visual Context,
CVPR17(1978-1987)
IEEE DOI
1711
Bioinformatics, Genomics, Object detection, Proposals, Semantics,
Training, Visualization
BibRef
Lu, J.,
Xiong, C.,
Parikh, D.,
Socher, R.,
Knowing When to Look: Adaptive Attention via a Visual Sentinel for
Image Captioning,
CVPR17(3242-3250)
IEEE DOI
1711
Adaptation models, Computational modeling, Context modeling,
Decoding, Logic gates, Mathematical model, Visualization
BibRef
Yao, T.,
Pan, Y.,
Li, Y.,
Mei, T.,
Incorporating Copying Mechanism in Image Captioning for Learning
Novel Objects,
CVPR17(5263-5271)
IEEE DOI
1711
Decoding, Hidden Markov models, Object recognition,
Recurrent neural networks, Standards, Training, Visualization
BibRef
Chen, L.,
Zhang, H.,
Xiao, J.,
Nie, L.,
Shao, J.,
Liu, W.,
Chua, T.S.,
SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks
for Image Captioning,
CVPR17(6298-6306)
IEEE DOI
1711
Detectors, Feature extraction, Image coding, Neural networks,
Semantics, Visualization
BibRef
Park, C.C.,
Kim, B.,
Kim, G.,
Attend to You: Personalized Image Captioning with Context Sequence
Memory Networks,
CVPR17(6432-6440)
IEEE DOI
1711
Pattern, recognition
BibRef
Sun, Q.,
Lee, S.,
Batra, D.,
Bidirectional Beam Search: Forward-Backward Inference in Neural
Sequence Models for Fill-in-the-Blank Image Captioning,
CVPR17(7215-7223)
IEEE DOI
1711
Approximation algorithms, Computational modeling, Decoding,
History, Inference algorithms, Recurrent, neural, networks
BibRef
Wang, Y.,
Lin, Z.,
Shen, X.,
Cohen, S.,
Cottrell, G.W.,
Skeleton Key: Image Captioning by Skeleton-Attribute Decomposition,
CVPR17(7378-7387)
IEEE DOI
1711
Measurement, Recurrent neural networks, SPICE, Semantics, Skeleton, Training
BibRef
Zanfir, M.[Mihai],
Marinoiu, E.[Elisabeta],
Sminchisescu, C.[Cristian],
Spatio-Temporal Attention Models for Grounded Video Captioning,
ACCV16(IV: 104-119).
Springer DOI
1704
BibRef
Chen, T.H.[Tseng-Hung],
Zeng, K.H.[Kuo-Hao],
Hsu, W.T.[Wan-Ting],
Sun, M.[Min],
Video Captioning via Sentence Augmentation and Spatio-Temporal
Attention,
Assist16(I: 269-286).
Springer DOI
1704
BibRef
Tan, Y.H.[Ying Hua],
Chan, C.S.[Chee Seng],
phi-LSTM: A Phrase-Based Hierarchical LSTM Model for Image Captioning,
ACCV16(V: 101-117).
Springer DOI
1704
BibRef
Weiland, L.[Lydia],
Hulpus, I.[Ioana],
Ponzetto, S.P.[Simone Paolo],
Dietz, L.[Laura],
Using Object Detection, NLP, and Knowledge Bases to Understand the
Message of Images,
MMMod17(II: 405-418).
Springer DOI
1701
BibRef
Liu, Y.[Yu],
Guo, Y.M.[Yan-Ming],
Lew, M.S.[Michael S.],
What Convnets Make for Image Captioning?,
MMMod17(I: 416-428).
Springer DOI
1701
BibRef
Tran, K.,
He, X.,
Zhang, L.,
Sun, J.,
Rich Image Captioning in the Wild,
DeepLearn-C16(434-441)
IEEE DOI
1612
BibRef
Wang, Y.L.[Yi-Lin],
Wang, S.H.[Su-Hang],
Tang, J.L.[Ji-Liang],
Liu, H.[Huan],
Li, B.X.[Bao-Xin],
PPP: Joint Pointwise and Pairwise Image Label Prediction,
CVPR16(6005-6013)
IEEE DOI
1612
BibRef
Yatskar, M.[Mark],
Ordonez, V.,
Zettlemoyer, L.[Luke],
Farhadi, A.[Ali],
Commonly Uncommon: Semantic Sparsity in Situation Recognition,
CVPR17(6335-6344)
IEEE DOI
1711
BibRef
Earlier: A1, A3, A4, Only:
Situation Recognition: Visual Semantic Role Labeling for Image
Understanding,
CVPR16(5534-5542)
IEEE DOI
1612
Image recognition, Image representation, Predictive models,
Semantics, Tensile stress, Training
BibRef
Kottur, S.[Satwik],
Vedantam, R.[Ramakrishna],
Moura, J.M.F.[José M. F.],
Parikh, D.[Devi],
VisualWord2Vec (Vis-W2V):
Learning Visually Grounded Word Embeddings Using Abstract Scenes,
CVPR16(4985-4994)
IEEE DOI
1612
BibRef
Zhu, Y.,
Groth, O.,
Bernstein, M.,
Fei-Fei, L.,
Visual7W: Grounded Question Answering in Images,
CVPR16(4995-5004)
IEEE DOI
1612
BibRef
Zhang, P.,
Goyal, Y.,
Summers-Stay, D.,
Batra, D.,
Parikh, D.,
Yin and Yang: Balancing and Answering Binary Visual Questions,
CVPR16(5014-5022)
IEEE DOI
1612
BibRef
Venugopalan, S.[Subhashini],
Hendricks, L.A.[Lisa Anne],
Rohrbach, M.[Marcus],
Mooney, R.[Raymond],
Darrell, T.J.[Trevor J.],
Saenko, K.[Kate],
Captioning Images with Diverse Objects,
CVPR17(1170-1178)
IEEE DOI
1711
BibRef
Earlier: A2, A1, A3, A4, A6, A5:
Deep Compositional Captioning: Describing Novel Object Categories
without Paired Training Data,
CVPR16(1-10)
IEEE DOI
1612
Data models, Image recognition, Predictive models, Semantics,
Training, Visualization.
Novel objects not in training data.
BibRef
Johnson, J.[Justin],
Karpathy, A.[Andrej],
Fei-Fei, L.[Li],
DenseCap:
Fully Convolutional Localization Networks for Dense Captioning,
CVPR16(4565-4574)
IEEE DOI
1612
Both localize and describe salient regions in images in natural language.
BibRef
Wang, M.[Minsi],
Song, L.[Li],
Yang, X.K.[Xiao-Kang],
Luo, C.F.[Chuan-Fei],
A parallel-fusion RNN-LSTM architecture for image caption generation,
ICIP16(4448-4452)
IEEE DOI
1610
Computational modeling
deep convolutional networks and recurrent neural networks.
BibRef
Lin, X.[Xiao],
Parikh, D.[Devi],
Leveraging Visual Question Answering for Image-Caption Ranking,
ECCV16(II: 261-277).
Springer DOI
1611
BibRef
Earlier:
Don't just listen, use your imagination:
Leveraging visual common sense for non-visual tasks,
CVPR15(2984-2993)
IEEE DOI
1510
BibRef
You, Q.Z.[Quan-Zeng],
Jin, H.L.[Hai-Lin],
Wang, Z.W.[Zhao-Wen],
Fang, C.[Chen],
Luo, J.B.[Jie-Bo],
Image Captioning with Semantic Attention,
CVPR16(4651-4659)
IEEE DOI
1612
BibRef
Jia, X.[Xu],
Gavves, E.[Efstratios],
Fernando, B.[Basura],
Tuytelaars, T.[Tinne],
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ICCV15(2407-2415)
IEEE DOI
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Computer architecture
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Mind's eye:
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CVPR15(2422-2431)
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1510
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CVPR15(4566-4575)
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CVPR15(1473-1482)
IEEE DOI
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WACV14(1050-1057)
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1406
Clouds
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Chapter on Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants continues in
General References for Matching .