Awesome-Visual-Captioning

Table of Contents

• release papers AAAI-2021
• ACMMM-2020
• NeurIPS-2020
• ECCV-2020
• CVPR-2020
• ACL-2020
• AAAI-2020
• ACL-2019
• NeurIPS-2019
• ICCV-2019
• CVPR-2019
• AAAI-2019

Paper Roadmap

AAAI-2021

Image Captioning
- Partially Non-Autoregressive Image Captioning
- Improving Image Captioning by Leveraging Intra- and Inter-layer Global Representation in Transformer Network. [paper]
- Object Relation Attention for Image Paragraph Captioning
- Dual-Level Collaborative Transformer for Image Captioning
- Memory-Augmented Image Captioning
- Image Captioning with Context-Aware Auxiliary Guidance. [paper]
- Consensus Graph Representation Learning for Better Grounded Image Captioning
- FixMyPose: Pose Correctional Captioning and Retrieval
- 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
- Augmented Partial Mutual Learning with Frame Masking for Video Captioning

ACMMM-2020

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

oral

Video Captioning - Controllable Video Captioning with an Exemplar Sentence.

oral

oral

NeurIPS-2020

• 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]
  

ECCV-2020

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

oral

oral

oral

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

Spotlight

Spotlight

CVPR-2020

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

ACL-2020

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

AAAI-2020

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)

ACL-2019

• 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

NeurIPS-2019

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
  

ICCV-2019

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

CVPR-2019

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 JD.com)

• 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)

AAAI-2019

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 JD.com)
  

  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)