deepaliverma / awesome-video-captioning-1

A curated list of research papers in Video Captioning

Awesome-Video-Captioning

A curated list of research papers in Video Captioning(from 2015 to 2020). Link to the code and project website if available.

Contents

• 2015
• 2016
• 2017
• 2018
• 2019
• 2020
• Dense Captioning
• Grounded Captioning

Paper List

2015

1. LSTM-P: Translating Videos to Natural Language Using Deep Recurrent Neural Networks
   Subhashini Venugopalan, Huijuan Xu, Jeff Donahue, Marcus Rohrbach, Raymond Mooney, Kate Saenko
   NAACL, 2015.[caffe-code]

2. LRCN: Long-term Recurrent Convolutional Networks for Visual Recognition and Description
   Jeff Donahue, Lisa Anne Hendricks, Marcus Rohrbach, Subhashini Venugopalan, Sergio Guadarrama, Kate Saenko, Trevor Darrell
   CVPR, 2015.[website]

3. S2VT: Sequence to Sequence – Video to Text
   Subhashini Venugopalan, Marcus Rohrbach, Jeff Donahue, Raymond Mooney, Trevor Darrell, Kate Saenko
   ICCV, 2015.[caffe-code]

4. SA: Describing Videos by Exploiting Temporal Structure
   Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Pal, Hugo Larochelle, Aaron Courville
   ICCV, 2015.[theano-code] [tf-code]

2016

1. LSTM-E: Jointly Modeling Embedding and Translation to Bridge Video and Language
   Yingwei Pan, Tao Mei, Ting Yao, Houqiang Li, Yong Rui
   CVPR, 2016.

2. HRNE: Hierarchical Recurrent Neural Encoder for Video Representation with Application to Captioning
   Pingbo Pan, Zhongwen Xu, Yi Yang, Fei Wu, Yueting Zhuang
   CVPR, 2016.

3. h-RNN: Video Paragraph Captioning Using Hierarchical Recurrent Neural Networks
   Haonan Yu, Jiang Wang, Zhiheng Huang, Yi Yang, Wei Xu
   CVPR, 2016.

4. MSR-VTT: MSR-VTT: A Large Video Description Dataset for Bridging Video and Language
   Jun Xu , Tao Mei , Ting Yao and Yong Rui
   CVPR, 2016.[website]

5. BiLSTM: Video Description using Bidirectional Recurrent Neural Networks
   Álvaro Peris, Marc Bolaños, Petia Radeva, Francisco Casacuberta
   ICANN, 2016.

2017

1. DenseVidCap: Weakly Supervised Dense Video Captioning
   Zhiqiang Shen, Jianguo Li, Zhou Su, Minjun Li, Yurong Chen, Yu-Gang Jiang, Xiangyang Xue
   CVPR, 2017.[tf-code]

2. LSTM-TSA: Video Captioning with Transferred Semantic Attributes
   Yingwei Pan, Ting Yao, Houqiang Li, Tao Mei
   CVPR, 2017.

3. SCN: Semantic Compositional Networks for Visual Captioning
   Zhe Gan, Chuang Gan, Xiaodong He, Yunchen Pu, Kenneth Tran, Jianfeng Gao, Lawrence Carin, Li Deng
   CVPR, 2017.[theano-code]

4. StyleNet: StyleNet: Generating Attractive Visual Captions with Styles
   Chuang Gan, Zhe Gan, Xiaodong He, Jianfeng Gao, Li Deng
   CVPR, 2017.[pytorch-code]

5. CT-SAN: End-to-end Concept Word Detection for Video Captioning, Retrieval, and Question Answering
   Youngjae Yu, Hyungjin Ko, Jongwook Choi, Gunhee Kim
   CVPR, 2017.[tf-code]

6. CGVS: Top-down Visual Saliency Guided by Captions
   Vasili Ramanishka, Abir Das, Jianming Zhang, Kate Saenko
   CVPR, 2017.[tf-code]

7. HBA: Hierarchical Boundary-Aware Neural Encoder for Video Captioning
   Lorenzo Baraldi, Costantino Grana, Rita Cucchiara
   CVPR, 2017.[pytorch-code]

8. TDDF: Task-Driven Dynamic Fusion: Reducing Ambiguity in Video Description
   Xishan Zhang, Ke Gao, Yongdong Zhang, Dongming Zhang, Jintao Li,and Qi Tian
   CVPR, 2017.

9. GEAN: Supervising Neural Attention Models for Video Captioning by Human Gaze Data
   Youngjae Yu, Jongwook Choi, Yeonhwa Kim, Kyung Yoo, Sang-Hun Lee, Gunhee Kim
   CVPR, 2017.[tf-code]

10. MM-Att: Attention-Based Multimodal Fusion for Video Description
    Chiori Hori, Takaaki Hori, Teng-Yok Lee, Kazuhiro Sumi, John R. Hershey, Tim K. Marks
    ICCV, 2017.

11. Tessellation: Temporal Tessellation: A Unified Approach for Video Analysis
    Dotan Kaufman, Gil Levi, Tal Hassner, Lior Wolf
    ICCV, 2017.[tf-code]

12. MTEG: Multi-Task Video Captioning with Video and Entailment Generation
    Ramakanth Pasunuru, Mohit Bansal
    ACL, 2017.

13. MAM-RNN: MAM-RNN: Multi-level Attention Model Based RNN for Video Captioning
    Xuelong Li, Bin Zhao, Xiaoqiang Lu
    IJCAI, 2017.

14. hLSTMat: Hierarchical LSTM with Adjusted Temporal Attention for Video Captioning
    Jingkuan Song, Lianli Gao, Zhao Guo, Wu Liu, Dongxiang Zhang, Heng Tao Shen
    IJCAI, 2017.[theano-code]

2018

1. Survey: Study of Video Captioning Problem
   Jiaqi Su
   cos598B, 2018.

2. Fine-grained Video Captioning for Sports Narrative
   Huanyu Yu, Shuo Cheng, Bingbing Ni, Minsi Wang, Jian Zhang, Xiaokang Yang
   CVPR, 2018.

3. TSA-ED: Interpretable Video Captioning via Trajectory Structured Localization
   Xian Wu, Guanbin Li Qingxing Cao, Qingge Ji, Liang Lin
   CVPR, 2018.

4. RecNet: Reconstruction Network for Video Captioning
   Bairui Wang, Lin Ma, Wei Zhang, Wei Liu
   CVPR, 2018.[pytorch-code]

5. M3: M3: Multimodal Memory Modelling for Video Captioning
   Junbo Wang, Wei Wang, Yan Huang, Liang Wang, Tieniu Tan
   CVPR, 2018.

6. PickNet: Less Is More: Picking Informative Frames for Video Captioning
   Yangyu Chen, Shuhui Wang, Weigang Zhang, Qingming Huang
   ECCV, 2018.

7. ECO-SCN: ECO: Efficient Convolutional Network for Online Video Understanding
   Mohammadreza Zolfaghari, Kamaljeet Singh, Thomas Brox
   ECCV, 2018.[caffe-code] [pytorch-code]

8. SibNet: SibNet: Sibling Convolutional Encoder for Video Captioning
   Sheng liu, Zhou Ren, Junsong Yuan
   ACM MM, 2018.

9. TubeNet: Video Captioning with Tube Features
   Bin Zhao, Xuelong Li, Xiaoqiang Lu
   IJCAI, 2018.

2019

1. Survey: Video Description: A Survey of Methods, Datasets and Evaluation Metrics
   Nayyer Aafaq, Ajmal Mian, Wei Liu, Syed Zulqarnain Gilani, Mubarak Shah
   ACM Computing Surveys, 2019.

2. GRU-EVE: Spatio-Temporal Dynamics and Semantic Attribute Enriched Visual Encoding for Video Captioning
   Nayyer Aafaq, Naveed Akhtar, Wei Liu, Syed Zulqarnain Gilani, Ajmal Mian
   CVPR, 2019.

3. MARN: Memory-Attended Recurrent Network for Video Captioning
   Wenjie Pei, Jiyuan Zhang, Xiangrong Wang, Lei Ke, Xiaoyong Shen, Yu-Wing Tai
   CVPR, 2019.

4. OA-BTG: Object-aware Aggregation with Bidirectional Temporal Graph for Video Captioning
   Junchao Zhang, Yuxin Peng
   CVPR, 2019.

5. VATEX: VaTeX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research
   Xin Wang, Jiawei Wu, Junkun Chen, Lei Li, Yuan-Fang Wang, William Yang Wang
   ICCV, 2019.[website]

6. POS: Joint Syntax Representation Learning and Visual Cue Translation for Video Captioning
   Jingyi Hou, Xinxiao Wu, Wentian Zhao, Jiebo Luo, Yunde Jia
   ICCV, 2019.

7. POS-CG: Controllable Video Captioning With POS Sequence Guidance Based on Gated Fusion Network
   Bairui Wang, Lin Ma, Wei Zhang, Wenhao Jiang, Jingwen Wang, Wei Liu
   ICCV, 2019.[pytorch-code]

8. WIT: Watch It Twice: Video Captioning with a Refocused Video Encoder
   Xiangxi Shi, Jianfei Cai, Shafiq Joty, Jiuxiang Gu
   ACM MM, 2019.

9. MGSA: Motion Guided Spatial Attention for Video Captioning
   Shaoxiang Chen and Yu-Gang Jiang
   AAAI, 2019.

10. TDConvED: Temporal Deformable Convolutional Encoder-Decoder Networks for Video Captioning
    Jingwen Chen, Yingwei Pan, Yehao Li, Ting Yao, Hongyang Chao, Tao Mei
    AAAI, 2019.

11. FCVC-CF&IA: Fully Convolutional Video Captioning with Coarse-to-Fine and Inherited Attention
    Kuncheng Fang, Lian Zhou, Cheng Jin, Yuejie Zhang,Kangnian Weng,Tao Zhang, Weiguo Fan
    AAAI, 2019.

12. TAMoE: Learning to Compose Topic-Aware Mixture of Experts for Zero-Shot Video Captioning
    Xin Wang, Jiawei Wu, Da Zhang, Yu Su, William Yang Wang
    AAAI, 2019.[code]

13. VIC: Video Interactive Captioning with Human Prompts
    Aming Wu, Yahong Han and Yi Yang
    IJCAI, 2019.[code]

2020

1. Spatio-Temporal Graph for Video Captioning with Knowledge Distillation
   Boxiao Pan, Haoye Cai, De-An Huang, Kuan-Hui Lee, Adrien Gaidon, Ehsan Adeli, Juan Carlos Niebles
   CVPR, 2020.

2. SAAT: Syntax-Aware Action Targeting for Video Captioning
   Zheng, Qi and Wang, Chaoyue and Tao, Dacheng
   CVPR, 2020.[pytorch-code]

3. ORG-TRL: Object Relational Graph with Teacher-Recommended Learning for Video Captioning
   Ziqi Zhang, Yaya Shi, Chunfeng Yuan, Bing Li, Peijin Wang, Weiming Hu, Zhengjun Zha
   CVPR, 2020.

4. PMI-CAP: Learning Modality Interaction for Temporal Sentence Localization and Event Captioning in Videos
   Shaoxiang Chen, Wenhao Jiang, Wei Liu, Yu-Gang Jiang
   ECCV, 2020.[pytorch-code]

5. RMN: Learning to Discretely Compose Reasoning Module Networks for Video Captioning
   Ganchao Tan, Daqing Liu, Meng Wang and Zheng-Jun Zha
   IJCAI, 2020.[pytorch-code]

6. SBAT: SBAT: Video Captioning with Sparse Boundary-Aware Transformer
   Tao Jin, Siyu Huang, Yingming Li, Zhongfei Zhang, Ming Chen
   IJCAI, 2020.

7. Joint Commonsense and Relation Reasoning for Image and Video Captioning
   Jingyi Hou, Xinxiao Wu, Xiaoxun Zhang, Yayun Qi, Yunde Jia, Jiebo Luo
   AAAI, 2020.

8. SMCG: Controllable Video Captioning with an Exemplar Sentence
   Yitian Yuan, Lin Ma, Jingwen Wang, Wenwu Zhu
   ACM MM, 2020.

9. Poet: Poet: Product-oriented Video Captioner for E-commerce
   Shengyu Zhang, Ziqi Tan, Jin Yu, Zhou Zhao, Kun Kuang, Jie Liu, Jingren Zhou, Hongxia Yang, Fei Wu
   ACM MM, 2020.

10. Learning Semantic Concepts and Temporal Alignment for Narrated Video Procedural Captioning
    Botian Shi, Lei Ji, Zhendong Niu, Nan Duan, Ming Zhou, Xilin Chen
    ACM MM, 2020.

Dense-Captioning

1. Dense-Captioning Events in Videos
   Ranjay Krishna, Kenji Hata, Frederic Ren, Li Fei-Fei, Juan Carlos Niebles
   ICCV, 2017.[code] [website]

2. End-to-End Dense Video Captioning with Masked Transformer
   Luowei Zhou, Yingbo Zhou, Jason J. Corso, Richard Socher, Caiming Xiong
   CVPR, 2018.[pytorch-code]

3. Attend and Interact: Higher-Order Object Interactions for Video Understanding
   Chih-Yao Ma, Asim Kadav, Iain Melvin, Zsolt Kira, Ghassan AlRegib, and Hans Peter Graf
   CVPR, 2018.

4. Jointly Localizing and Describing Events for Dense Video Captioning
   Yehao Li, Ting Yao, Yingwei Pan, Hongyang Chao, Tao Mei
   CVPR, 2018.

5. Bidirectional Attentive Fusion with Context Gating for Dense Video Captioning
   Jingwen Wang, Wenhao Jiang, Lin Ma, Wei Liu, Yong Xu
   CVPR, 2018.[tf-code]

6. Move Forward and Tell: A Progressive Generator of Video Descriptions
   Yilei Xiong, Bo Dai, Dahua Lin
   ECCV, 2018.

7. Adversarial Inference for Multi-sentence Video Description
   Jae Sung Park, Marcus Rohrbach, Trevor Darrell, Anna Rohrbach
   CVPR, 2019.[pytorch-code]

8. Dense Relational Captioning: Triple-stream Networks for Relationship-based Captioning
   Dong-Jin Kim, Jinsoo Choi, Tae-Hyun Oh, In So Kweon
   CVPR, 2019.[torch-code]

9. Streamlined Dense Video Captioning
   Jonghwan Mun, Linjie Yang, Zhou Ren, Ning Xu, Bohyung Han
   CVPR, 2019.

10. Watch, Listen and Tell: Multi-Modal Weakly Supervised Dense Event Captioning
    Tanzila Rahman, Bicheng Xu, Leonid Sigal
    ICCV, 2019.

11. An Efficient Framework for Dense Video Captioning
    Maitreya Suin, A. N. Rajagopalan
    AAAI, 2020.

12. MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning
    Jie Lei, Liwei Wang, Yelong Shen, Dong Yu, Tamara L. Berg, Mohit Bansal
    ACL, 2020. [pytorch-code]

13. Identity-Aware Multi-Sentence Video Description
    Jae Sung Park, Trevor Darrell, Anna Rohrbach
    ECCV, 2020.

Grounded-Captioning

1. GVD: Grounded Video Description
   Luowei Zhou, Yannis Kalantidis, Xinlei Chen, Jason J. Corso, Marcus Rohrbach
   CVPR, 2019.[pytorch-code]

2. Relational Graph Learning for Grounded Video Description Generation
   Wenqiao Zhang, Xineric Wang, Siliang Tang, Haizhou Shi, Haochen Shi, Jun Xiao, Yueting Zhuang, Williamyang Wang
   ACM MM, 2020.