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This repository focus on Image Captioning & Video Captioning & Seq-to-Seq Learning & NLP

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Table of Contents

Paper Roadmap


Image Captioning - Control Image Captioning Spatially and Temporally
- SMURF: SeMantic and linguistic UndeRstanding Fusion for Caption Evaluation via Typicality Analysis [paper] [code]
- Enhancing Descriptive Image Captioning with Natural Language Inference
- UMIC: An Unreferenced Metric for Image Captioning via Contrastive Learning [paper]
- Semantic Relation-aware Difference Representation Learning for Change Captioning

Video Captioning - Hierarchical Context-aware Network for Dense Video Event Captioning
- Video Paragraph Captioning as a Text Summarization Task
- O2NA: An Object-Oriented Non-Autoregressive Approach for Controllable Video Captioning


Image Captioning
- Connecting What to Say With Where to Look by Modeling Human Attention Traces. [paper] [code]
- Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles. [paper]
- Improving OCR-Based Image Captioning by Incorporating Geometrical Relationship. [paper]
- Image Change Captioning by Learning From an Auxiliary Task. [paper]
- Scan2Cap: Context-aware Dense Captioning in RGB-D Scans. [paper] [code]
- Towards Bridging Event Captioner and Sentence Localizer for Weakly Supervised Dense Event Captioning. paper - TAP: Text-Aware Pre-Training for Text-VQA and Text-Caption. [paper]
- Towards Accurate Text-Based Image Captioning With Content Diversity Exploration. [paper]
- FAIEr: Fidelity and Adequacy Ensured Image Caption Evaluation. [paper]
- RSTNet: Captioning With Adaptive Attention on Visual and Non-Visual Words. [paper]
- Human-Like Controllable Image Captioning With Verb-Specific Semantic Roles. [paper]

Video Captioning - Open-Book Video Captioning With Retrieve-Copy-Generate Network. [paper]
- Towards Diverse Paragraph Captioning for Untrimmed Videos. [paper]


Image Captioning
- Partially Non-Autoregressive Image Captioning. [code]
- Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network. [paper]
- Object Relation Attention for Image Paragraph Captioning [paper]
- Dual-Level Collaborative Transformer for Image Captioning. [paper] [code]
- Memory-Augmented Image Captioning [paper]
- Image Captioning with Context-Aware Auxiliary Guidance. [paper]
- Consensus Graph Representation Learning for Better Grounded Image Captioning. [paper]
- FixMyPose: Pose Correctional Captioning and Retrieval. [paper] [code] [website]
- VIVO: Visual Vocabulary Pre-Training for Novel Object Captioning [paper]

Video Captioning - Non-Autoregressive Coarse-to-Fine Video Captioning. [paper]
- Semantic Grouping Network for Video Captioning. [paper] [code]
- Augmented Partial Mutual Learning with Frame Masking for Video Captioning. [paper]


Image Captioning - Structural Semantic Adversarial Active Learning for Image Captioning.

- Iterative Back Modification for Faster Image Captioning. [paper]
- Bridging the Gap between Vision and Language Domains for Improved Image Captioning. [paper]
- Hierarchical Scene Graph Encoder-Decoder for Image Paragraph Captioning. [paper]
- Improving Intra- and Inter-Modality Visual Relation for Image Captioning. [paper]
- ICECAP: Information Concentrated Entity-aware Image Captioning. [paper]
- Attacking Image Captioning Towards Accuracy-Preserving Target Words Removal. [paper]
- Multimodal Attention with Image Text Spatial Relationship for OCR-Based Image Captioning. [paper]

Video Captioning - Controllable Video Captioning with an Exemplar Sentence.

- Poet: Product-oriented Video Captioner for E-commerce.
- Learning Semantic Concepts and Temporal Alignment for Narrated Video Procedural Captioning. [paper]
- Relational Graph Learning for Grounded Video Description Generation. [paper]


  • Prophet Attention: Predicting Attention with Future Attention for Improved Image Captioning. [paper]
  • RATT: Recurrent Attention to Transient Tasks for Continual Image Captioning. [paper]
  • Diverse Image Captioning with Context-Object Split Latent Spaces. [paper]


Image Captioning - Compare and Reweight: Distinctive Image Captioning Using Similar Images Sets.

[paper] - In-Home Daily-Life Captioning Using Radio Signals.
[paper] [website] - TextCaps: a Dataset for Image Captioning with Reading Comprehension.
[paper] [website] [code] - SODA: Story Oriented Dense Video Captioning Evaluation Framework. [paper] - Towards Unique and Informative Captioning of Images. [paper] - Learning Visual Representations with Caption Annotations. [paper] [website] - Fashion Captioning: Towards Generating Accurate Descriptions with Semantic Rewards. [paper] - Length Controllable Image Captioning. [paper] [code] - Comprehensive Image Captioning via Scene Graph Decomposition. [paper] [website] - Finding It at Another Side: A Viewpoint-Adapted Matching Encoder for Change Captioning. [paper] - Captioning Images Taken by People Who Are Blind. [paper] - Learning to Generate Grounded Visual Captions without Localization Supervision. [paper] [code]

Video Captioning - Learning Modality Interaction for Temporal Sentence Localization and Event Captioning in Videos.

[paper] [code] - Character Grounding and Re-Identification in Story of Videos and Text Descriptions.
[paper] [code] - Identity-Aware Multi-Sentence Video Description. [paper]


Image Captioning

  • Context-Aware Group Captioning via Self-Attention and Contrastive Features [paper]
    Zhuowan Li, Quan Tran, Long Mai, Zhe Lin, Alan L. Yuille
  • More Grounded Image Captioning by Distilling Image-Text Matching Model [paper] [code]
    Yuanen Zhou, Meng Wang, Daqing Liu, Zhenzhen Hu, Hanwang Zhang
  • Show, Edit and Tell: A Framework for Editing Image Captions [paper] [code]
    Fawaz Sammani, Luke Melas-Kyriazi
  • Say As You Wish: Fine-Grained Control of Image Caption Generation With Abstract Scene Graphs [paper] [code]
    Shizhe Chen, Qin Jin, Peng Wang, Qi Wu
  • Normalized and Geometry-Aware Self-Attention Network for Image Captioning [paper]
    Longteng Guo, Jing Liu, Xinxin Zhu, Peng Yao, Shichen Lu, Hanqing Lu
  • Meshed-Memory Transformer for Image Captioning [paper] [code]
    Marcella Cornia, Matteo Stefanini, Lorenzo Baraldi, Rita Cucchiara
  • X-Linear Attention Networks for Image Captioning [paper] [code]
    Yingwei Pan, Ting Yao, Yehao Li, Tao Mei
  • Transform and Tell: Entity-Aware News Image Captioning [paper] [code] [website]
    Alasdair Tran, Alexander Mathews, Lexing Xie

Video Captioning

  • Object Relational Graph With Teacher-Recommended Learning for Video Captioning [paper]
    Ziqi Zhang, Yaya Shi, Chunfeng Yuan, Bing Li, Peijin Wang, Weiming Hu, Zheng-Jun Zha

  • Spatio-Temporal Graph for Video Captioning With Knowledge Distillation [paper] [code]
    Boxiao Pan, Haoye Cai, De-An Huang, Kuan-Hui Lee, Adrien Gaidon, Ehsan Adeli, Juan Carlos Niebles

  • Better Captioning With Sequence-Level Exploration [paper]
    Jia Chen, Qin Jin

  • Syntax-Aware Action Targeting for Video Captioning [code]
    Qi Zheng, Chaoyue Wang, Dacheng Tao


Image Captioning

  • Clue: Cross-modal Coherence Modeling for Caption Generation [paper]
    Malihe Alikhani, Piyush Sharma, Shengjie Li, Radu Soricut and Matthew Stone

  • Improving Image Captioning Evaluation by Considering Inter References Variance [paper]
    Yanzhi Yi, Hangyu Deng and Jinglu Hu

  • Improving Image Captioning with Better Use of Caption [paper] [code]
    Zhan Shi, Xu Zhou, Xipeng Qiu and Xiaodan Zhu

Video Captioning

  • MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning [paper] [code]
    Jie Lei, Liwei Wang, Yelong Shen, Dong Yu, Tamara Berg and Mohit Bansal


Image Captioning

  • Unified VLP: Unified Vision-Language Pre-Training for Image Captioning and VQA [paper]
    Luowei Zhou (University of Michigan); Hamid Palangi (Microsoft Research); Lei Zhang (Microsoft); Houdong Hu (Microsoft AI and Research); Jason Corso (University of Michigan); Jianfeng Gao (Microsoft Research)

  • OffPG: Reinforcing an Image Caption Generator using Off-line Human Feedback [paper]
    Paul Hongsuck Seo (POSTECH); Piyush Sharma (Google Research); Tomer Levinboim (Google); Bohyung Han(Seoul National University); Radu Soricut (Google)

  • MemCap: Memorizing Style Knowledge for Image Captioning [paper]
    Wentian Zhao (Beijing Institute of Technology); Xinxiao Wu (Beijing Institute of Technology); Xiaoxun Zhang(Alibaba Group)

  • C-R Reasoning: Joint Commonsense and Relation Reasoning for Image and Video Captioning [paper]
    Jingyi Hou (Beijing Institute of Technology); Xinxiao Wu (Beijing Institute of Technology); Xiaoxun Zhang (AlibabaGroup); Yayun Qi (Beijing Institute of Technology); Yunde Jia (Beijing Institute of Technology); Jiebo Luo (University of Rochester)

  • MHTN: Learning Long- and Short-Term User Literal-Preference with Multimodal Hierarchical Transformer Network for Personalized Image Caption [paper]
    Wei Zhang (East China Normal University); Yue Ying (East China Normal University); Pan Lu (The University of California, Los Angeles); Hongyuan Zha (GEORGIA TECH)

  • Show, Recall, and Tell: Image Captioning with Recall Mechanism [paper]
    Li WANG (MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, China); Zechen BAI(Institute of Software, Chinese Academy of Science, China); Yonghua Zhang (Bytedance); Hongtao Lu (Shanghai Jiao Tong University)

  • Interactive Dual Generative Adversarial Networks for Image Captioning
    Junhao Liu (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences); Kai Wang (Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences); Chunpu Xu (Huazhong University of Science and Technology); Zhou Zhao (Zhejiang University); Ruifeng Xu (Harbin Institute of Technology (Shenzhen)); Ying Shen (Peking University Shenzhen Graduate School); Min Yang ( Chinese Academy of Sciences)

  • FDM-net: Feature Deformation Meta-Networks in Image Captioning of Novel Objects [paper]
    Tingjia Cao (Fudan University); Ke Han (Fudan University); Xiaomei Wang (Fudan University); Lin Ma (Tencent AI Lab); Yanwei Fu (Fudan University); Yu-Gang Jiang (Fudan University); Xiangyang Xue (Fudan University)

Video Captioning

  • An Efficient Framework for Dense Video Captioning
    Maitreya Suin (Indian Institute of Technology Madras)*; Rajagopalan Ambasamudram (Indian Institute of Technology Madras)


  • Informative Image Captioning with External Sources of Information [paper]
    Sanqiang Zhao, Piyush Sharma, Tomer Levinboim and Radu Soricut

  • Dense Procedure Captioning in Narrated Instructional Videos [paper]
    Botian Shi, Lei Ji, Yaobo Liang, Nan Duan, Peng Chen, Zhendong Niu and Ming Zhou

  • Bridging by Word: Image Grounded Vocabulary Construction for Visual Captioning [paper]
    Zhihao Fan, Zhongyu Wei, Siyuan Wang and Xuanjing Huang

  • Bridging by Word: Image Grounded Vocabulary Construction for Visual Captioning [paper]
    Zhihao Fan, Zhongyu Wei, Siyuan Wang and Xuanjing Huang

  • Generating Question Relevant Captions to Aid Visual Question Answering [paper]
    Jialin Wu, Zeyuan Hu and Raymond Mooney

  • Bridging by Word: Image Grounded Vocabulary Construction for Visual Captioning [paper]
    Zhihao Fan, Zhongyu Wei, Siyuan Wang and Xuanjing Huang


Image Captioning

  • AAT: Adaptively Aligned Image Captioning via Adaptive Attention Time [paper] [code]
    Lun Huang, Wenmin Wang, Yaxian Xia, Jie Chen
  • ObjRel Transf: Image Captioning: Transforming Objects into Words [paper] [code]
    Simao Herdade, Armin Kappeler, Kofi Boakye, Joao Soares
  • VSSI-cap: Variational Structured Semantic Inference for Diverse Image Captioning [paper]
    Fuhai Chen, Rongrong Ji, Jiayi Ji, Xiaoshuai Sun, Baochang Zhang, Xuri Ge, Yongjian Wu, Feiyue Huang


Video Captioning

  • VATEX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research [paper] [challenge]
    Xin Wang, Jiawei Wu, Junkun Chen, Lei Li, Yuan-Fang Wang, William Yang Wang

    ICCV 2019 Oral
  • POS+CG: Controllable Video Captioning With POS Sequence Guidance Based on Gated Fusion Network [paper]
    Bairui Wang, Lin Ma, Wei Zhang, Wenhao Jiang, Jingwen Wang, Wei Liu

  • POS: Joint Syntax Representation Learning and Visual Cue Translation for Video Captioning [paper]
    Jingyi Hou, Xinxiao Wu, Wentian Zhao, Jiebo Luo, Yunde Jia

Image Captioning

  • DUDA: Robust Change Captioning
    Dong Huk Park, Trevor Darrell, Anna Rohrbach [paper]

    ICCV 2019 Oral
  • AoANet: Attention on Attention for Image Captioning [paper]
    Lun Huang, Wenmin Wang, Jie Chen, Xiao-Yong Wei

    ICCV 2019 Oral
  • MaBi-LSTMs: Exploring Overall Contextual Information for Image Captioning in Human-Like Cognitive Style [paper]
    Hongwei Ge, Zehang Yan, Kai Zhang, Mingde Zhao, Liang Sun

  • Align2Ground: Align2Ground: Weakly Supervised Phrase Grounding Guided by Image-Caption Alignment [paper]
    Samyak Datta, Karan Sikka, Anirban Roy, Karuna Ahuja, Devi Parikh, Ajay Divakaran*

  • GCN-LSTM+HIP: Hierarchy Parsing for Image Captioning [paper]
    Ting Yao, Yingwei Pan, Yehao Li, Tao Mei

  • IR+Tdiv: Generating Diverse and Descriptive Image Captions Using Visual Paraphrases [paper]
    Lixin Liu, Jiajun Tang, Xiaojun Wan, Zongming Guo

  • CNM+SGAE: Learning to Collocate Neural Modules for Image Captioning [paper]
    Xu Yang, Hanwang Zhang, Jianfei Cai

  • Seq-CVAE: Sequential Latent Spaces for Modeling the Intention During Diverse Image Captioning [paper]
    Jyoti Aneja, Harsh Agrawal, Dhruv Batra, Alexander Schwing

  • Towards Unsupervised Image Captioning With Shared Multimodal Embeddings [paper]
    Iro Laina, Christian Rupprecht, Nassir Navab

  • Human Attention in Image Captioning: Dataset and Analysis [paper]
    Sen He, Hamed R. Tavakoli, Ali Borji, Nicolas Pugeault

  • RDN: Reflective Decoding Network for Image Captioning [paper]
    Lei Ke, Wenjie Pei, Ruiyu Li, Xiaoyong Shen, Yu-Wing Tai

  • PSST: Joint Optimization for Cooperative Image Captioning [paper]
    Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik

  • MUTAN: Watch, Listen and Tell: Multi-Modal Weakly Supervised Dense Event Captioning [paper]
    Tanzila Rahman, Bicheng Xu, Leonid Sigal

  • ETA: Entangled Transformer for Image Captioning [paper]
    Guang Li, Linchao Zhu, Ping Liu, Yi Yang

  • nocaps: novel object captioning at scale [paper]
    Harsh Agrawal, Karan Desai, Yufei Wang, Xinlei Chen, Rishabh Jain, Mark Johnson, Dhruv Batra, Devi Parikh, Stefan Lee, Peter Anderson

  • Cap2Det: Learning to Amplify Weak Caption Supervision for Object Detection [paper]
    Keren Ye, Mingda Zhang, Adriana Kovashka, Wei Li, Danfeng Qin, Jesse Berent

  • Graph-Align: Unpaired Image Captioning via Scene Graph Alignments paper
    Jiuxiang Gu, Shafiq Joty, Jianfei Cai, Handong Zhao, Xu Yang, Gang Wang

  • : Learning to Caption Images Through a Lifetime by Asking Questions [paper]
    Tingke Shen, Amlan Kar, Sanja Fidler


Image Captioning

  • SGAE: Auto-Encoding Scene Graphs for Image Captioning [paper] [code]
    XU YANG (Nanyang Technological University); Kaihua Tang (Nanyang Technological University); Hanwang Zhang (Nanyang Technological University); Jianfei Cai (Nanyang Technological University)

    CVPR 2019 Oral
  • POS: Fast, Diverse and Accurate Image Captioning Guided by Part-Of-Speech [paper]
    Aditya Deshpande (University of Illinois at UC); Jyoti Aneja (University of Illinois, Urbana-Champaign); Liwei Wang (Tencent AI Lab); Alexander Schwing (UIUC); David Forsyth (Univeristy of Illinois at Urbana-Champaign)

    CVPR 2019 Oral
  • Unsupervised Image Captioning [paper] [code]
    Yang Feng (University of Rochester); Lin Ma (Tencent AI Lab); Wei Liu (Tencent); Jiebo Luo (U. Rochester)

  • Adversarial Attack to Image Captioning via Structured Output Learning With Latent Variables [paper]
    Yan Xu (UESTC); Baoyuan Wu (Tencent AI Lab); Fumin Shen (UESTC); Yanbo Fan (Tencent AI Lab); Yong Zhang (Tencent AI Lab); Heng Tao Shen (University of Electronic Science and Technology of China (UESTC)); Wei Liu (Tencent)

  • Describing like Humans: On Diversity in Image Captioning [paper]
    Qingzhong Wang (Department of Computer Science, City University of Hong Kong); Antoni Chan (City University of Hong Kong, Hong, Kong)

  • MSCap: Multi-Style Image Captioning With Unpaired Stylized Text [paper]
    Longteng Guo ( Institute of Automation, Chinese Academy of Sciences); Jing Liu (National Lab of Pattern Recognition, Institute of Automation,Chinese Academy of Sciences); Peng Yao (University of Science and Technology Beijing); Jiangwei Li (Huawei); Hanqing Lu (NLPR, Institute of Automation, CAS)

  • CapSal: Leveraging Captioning to Boost Semantics for Salient Object Detection [paper] [code]
    Lu Zhang (Dalian University of Technology); Huchuan Lu (Dalian University of Technology); Zhe Lin (Adobe Research); Jianming Zhang (Adobe Research); You He (Naval Aviation University)

  • Context and Attribute Grounded Dense Captioning [paper]
    Guojun Yin (University of Science and Technology of China); Lu Sheng (The Chinese University of Hong Kong); Bin Liu (University of Science and Technology of China); Nenghai Yu (University of Science and Technology of China); Xiaogang Wang (Chinese University of Hong Kong, Hong Kong); Jing Shao (Sensetime)

  • Dense Relational Captioning: Triple-Stream Networks for Relationship-Based Captioning [paper]
    Dong-Jin Kim (KAIST); Jinsoo Choi (KAIST); Tae-Hyun Oh (MIT CSAIL); In So Kweon (KAIST)

  • Show, Control and Tell: A Framework for Generating Controllable and Grounded Captions [paper]
    Marcella Cornia (University of Modena and Reggio Emilia); Lorenzo Baraldi (University of Modena and Reggio Emilia); Rita Cucchiara (Universita Di Modena E Reggio Emilia)

  • Self-Critical N-step Training for Image Captioning [paper]
    Junlong Gao (Peking University Shenzhen Graduate School); Shiqi Wang (CityU); Shanshe Wang (Peking University); Siwei Ma (Peking University, China); Wen Gao (PKU)

  • Look Back and Predict Forward in Image Captioning [paper]
    Yu Qin (Shanghai Jiao Tong University); Jiajun Du (Shanghai Jiao Tong University); Hongtao Lu (Shanghai Jiao Tong University); Yonghua Zhang (Bytedance)

  • Intention Oriented Image Captions with Guiding Objects [paper]
    Yue Zheng (Tsinghua University); Ya-Li Li (THU); Shengjin Wang (Tsinghua University)

  • Adversarial Semantic Alignment for Improved Image Captions [paper]
    Pierre Dognin (IBM); Igor Melnyk (IBM); Youssef Mroueh (IBM Research); Jarret Ross (IBM); Tom Sercu (IBM Research AI)

  • Good News, Everyone! Context driven entity-aware captioning for news images [paper] [code]
    Ali Furkan Biten (Computer Vision Center); Lluis Gomez (Universitat Autónoma de Barcelona); Marçal Rusiñol (Computer Vision Center, UAB); Dimosthenis Karatzas (Computer Vision Centre)

  • Pointing Novel Objects in Image Captioning [paper]
    Yehao Li (Sun Yat-Sen University); Ting Yao (JD AI Research); Yingwei Pan (JD AI Research); Hongyang Chao (Sun Yat-sen University); Tao Mei (AI Research of

  • Engaging Image Captioning via Personality [paper]
    Kurt Shuster (Facebook); Samuel Humeau (Facebook); Hexiang Hu (USC); Antoine Bordes (Facebook); Jason Weston (FAIR)

  • Intention Oriented Image Captions With Guiding Objects [paper]
    Yue Zheng, Yali Li, Shengjin Wang

  • Exact Adversarial Attack to Image Captioning via Structured Output Learning With Latent Variables [paper]
    Yan Xu, Baoyuan Wu, Fumin Shen, Yanbo Fan, Yong Zhang, Heng Tao Shen, Wei Liu

Video Captioning

  • SDVC: Streamlined Dense Video Captioning [paper]
    Jonghwan Mun (POSTECH); Linjie Yang (ByteDance AI Lab); Zhou Ren (Snap Inc.); Ning Xu (Snap); Bohyung Han (Seoul National University)

    CVPR 2019 Oral
  • GVD: Grounded Video Description [paper]
    Luowei Zhou (University of Michigan); Yannis Kalantidis (Facebook Research); Xinlei Chen (Facebook AI Research); Jason J Corso (University of Michigan); Marcus Rohrbach (Facebook AI Research)

    CVPR 2019 Oral
  • HybridDis: Adversarial Inference for Multi-Sentence Video Description [paper]
    Jae Sung Park (UC Berkeley); Marcus Rohrbach (Facebook AI Research); Trevor Darrell (UC Berkeley); Anna Rohrbach (UC Berkeley)

    CVPR 2019 Oral
  • OA-BTG: Object-aware Aggregation with Bidirectional Temporal Graph for Video Captioning [paper]
    Junchao Zhang (Peking University); Yuxin Peng (Peking University)

  • MARN: Memory-Attended Recurrent Network for Video Captioning [paper]
    Wenjie Pei (Tencent); Jiyuan Zhang (Tencent YouTu); Xiangrong Wang (Delft University of Technology); Lei Ke (Tencent); Xiaoyong Shen (Tencent); Yu-Wing Tai (Tencent)

  • GRU-EVE: Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning [paper]
    Nayyer Aafaq (The University of Western Australia); Naveed Akhtar (The University of Western Australia); Wei Liu (University of Western Australia); Syed Zulqarnain Gilani (The University of Western Australia); Ajmal Mian (University of Western Australia)


Image Captioning

  • Improving Image Captioning with Conditional Generative Adversarial Nets [paper]
    CHEN CHEN (Tencent); SHUAI MU (Tencent); WANPENG XIAO (Tencent); ZEXIONG YE (Tencent); LIESI WU (Tencent); QI JU (Tencent)
    AAAI 2019 Oral
  • PAGNet: Connecting Language to Images: A Progressive Attention-Guided Network for Simultaneous Image Captioning and Language Grounding [paper]
    Lingyun Song (Xi'an JiaoTong University); Jun Liu (Xi'an Jiaotong Univerisity); Buyue Qian (Xi'an Jiaotong University); Yihe Chen (University of Toronto)
    AAAI 2019 Oral
  • Meta Learning for Image Captioning [paper]
    Nannan Li (Wuhan University); Zhenzhong Chen (WHU); Shan Liu (Tencent America)
  • DA: Deliberate Residual based Attention Network for Image Captioning [paper] Lianli Gao (The University of Electronic Science and Technology of China); kaixuan fan (University of Electronic Science and Technology of China); Jingkuan Song (UESTC); Xianglong Liu (Beihang University); Xing Xu (University of Electronic Science and Technology of China); Heng Tao Shen (University of Electronic Science and Technology of China (UESTC))
  • HAN: Hierarchical Attention Network for Image Captioning [paper]
    Weixuan Wang (School of Electronic and Information Engineering, Sun Yat-sen University);Zhihong Chen (School of Electronic and Information Engineering, Sun Yat-sen University); Haifeng Hu (School of Electronic and Information Engineering, Sun Yat-sen University)
  • COCG: Learning Object Context for Dense Captioning [paper]
    Xiangyang Li (Institute of Computing Technology, Chinese Academy of Sciences); Shuqiang Jiang (ICT, China Academy of Science); Jungong Han (Lancaster University)

Video Captioning

  • TAMoE: Learning to Compose Topic-Aware Mixture of Experts for Zero-Shot Video Captioning [code] [paper]
    Xin Wang (University of California, Santa Barbara); Jiawei Wu (University of California, Santa Barbara); Da Zhang (UC Santa Barbara); Yu Su (OSU); William Wang (UC Santa Barbara)

    AAAI 2019 Oral
  • TDConvED: Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning [paper]
    Jingwen Chen (Sun Yat-set University); Yingwei Pan (JD AI Research); Yehao Li (Sun Yat-Sen University); Ting Yao (JD AI Research); Hongyang Chao (Sun Yat-sen University); Tao Mei (AI Research of

    AAAI 2019 Oral
  • FCVC-CF&IA: Fully Convolutional Video Captioning with Coarse-to-Fine and Inherited Attention [paper]
    Kuncheng Fang (Fudan University); Lian Zhou (Fudan University); Cheng Jin (Fudan University); Yuejie Zhang (Fudan University); Kangnian Weng (Shanghai University of Finance and Economics); Tao Zhang (Shanghai University of Finance and Economics); Weiguo Fan (University of Iowa)

  • MGSA: Motion Guided Spatial Attention for Video Captioning [paper]
    Shaoxiang Chen (Fudan University); Yu-Gang Jiang (Fudan University)

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