awesome-activity-prediction

by chinancheng

Paper list of activity prediction and related area

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Awesome Activity Prediction: Awesome

A paper list of Activity Prediction and related area resources, inspired by awesome-computer-vision and awesome-action-recognition.

Contents

Action Prediction In Early Stage

  • Predicting the Future: A Jointly Learnt Model for Action Anticipation [Paper]
    • H. Gammulle, S. Denman, S. Sridharan, C. Fookes, ICCV 2019
  • Spatiotemporal Feature Residual Propagation for Action Prediction [Paper]
    • H. Zhao, R. P. Wildes, ICCV 2019
  • Relational Action Forecasting [Paper]
    • C. Sun, A. Shrivastava, C. Vondrick, R. Sukthankar, K. Murphy, C. Schmid, CVPR 2019
  • Progressive Teacher-student Learning for Early Action Prediction [Paper]
    • X. Wang, J. F. Hu, J. H. Lai, J. Zhang, W. S. Zheng, CVPR 2019
  • Action Anticipation with RBF Kernelized Feature Mapping RNN [Paper]
    • Y. Shi, B. Fernando, R. Hartley, ECCV 2018
  • Part-Activated Deep Reinforcement Learning for Action Prediction [Paper]
    • L. Chen, J. Lu, Z. Song, J. Zhou, ECCV 2018
  • Temporal Relational Reasoning in Videos [Paper] [Project] [Code]
    • B. Zhou, A. Andonian, A. Oliva, A. Torralba, ECCV 2018
  • Human Action Recognition and Prediction: A Survey [Paper]
    • Y. Kong, Y. Fu, arxiv 2018
  • SSNet: Scale Selection Network for Online 3D Action Prediction [Paper]
    • J. Liu, A. Shahroudy, G. Wang, L. Y. Duan, A. C. Kot, CVPR 2018
  • Action Prediction from Videos via Memorizing Hard-to-Predict Samples [Paper]
    • Y. Kong, S. Gao, B. Sun, Y. Fu, AAAI 2018
  • On Encoding Temporal Evolution for Real-time Action Prediction [Paper]
    • F. Rezazadegan, S.Shirazi, M. Baktashmotlagh, L. S. Davis, arXiv 2018
  • Predictive Learning: Using Future Representation Learning Variantial Autoencoder for Human Action Prediction [Paper]    
    • Y. Runsheng, S. Zhenyu, M. Qiongxiong, Q. Laiyun, arXiv 2017
  • Encouraging LSTMs to Anticipate Actions Very Early [Paper]
    • M. S. Aliakbarian, F. Saleh, M. Salzmann, B. Fernando, L. Petersson, L. Andersson, ICCV 2017
  • Online Real-time Multiple Spatiotemporal Action Localisation and Prediction [Paper] [Code]
    • G. Singh, S. Saha, M. Sapienza, P. Torr, F. Cuzzolin, ICCV 2017
  • Visual Forecasting by Imitating Dynamics in Natural Sequences [Paper]
    • K. H. Zeng, W. B. Shen, D. A. Huang, M. Sun, J. C. Niebles, ICCV 2017
  • Binary Coding for Partial Action Analysis with Limited Observation Ratios [Paper]
    • J. Qin, L. Liu, L. Shao, B. Ni, C. Chen, F. Shen, Y. Wang, CVPR 2017
  • Deep Sequential Context Networks for Action Prediction [Paper]
    • Y. Kong, Z. Tao, Y. Fu, CVPR 2017
  • RED: Reinforced Encoder-Decoder Networks for Action Anticipation [Paper]
    • J. Gao, Z. Yang, R. Nevatia, BMVC 2017
  • Anticipating Visual Representations from Unlabeled Video [Paper]
    • C. Vondrick, H. Pirsiavash, A. Torralba, CVPR 2016
  • Learning Activity Progression in LSTMs for Activity Detection and Early Detection [Paper]
    • S. Ma, L. Sigal, S. Sclaroff, CVPR 2016
  • Deep Action- and Context-Aware Sequence Learning for Activity Recognition and Anticipation [Paper]
    • M. S. Aliakbarian, F. Saleh, B. Fernando, M. Salzmann, L. Petersson, L. Andersson, arxiv 2016
  • A hierarchical representation for future action prediction [Paper]
    • T. Lan, T. C. Chen, and S. Savarese, ECCV 2014
  • A Discriminative Model with Multiple Temporal Scales for Action Prediction [Paper]
    • Y. Kong, D. Kit, Y. Fu, ECCV 2014
  • Human activity prediction: Early recognition of ongoing activities from streaming videos [Paper]
    • M. S. Ryoo, ICCV 2011

Activity Prediction

  • Zero-Shot Anticipation for Instructional Activities [Paper]
    • F. Sener, A. Yao, ICCV 2019
  • Time-Conditioned Action Anticipation in One Shot [Paper]
    • Q. Ke, M. Fritz, B. Schiele, CVPR 2019
  • Peeking into the Future: Predicting Future Person Activities and Locations in Videos [Paper] [Code]
    • J. Liang, L. Jiang, J.C. Niebles, A. Hauptmann, L. Fei-Fei, CVPR 2019
  • Egocentric Activity Prediction via Event Modulated Attention [Paper]
    • Y. Shen, B. Ni, Z. Li, N. Zhuang, ECCV 2018
  • When will you do what? - Anticipating Temporal Occurrences of Activities [Paper] [Code]
    • Y. A. Farha, A. Richard, J. Gall, CVPR 2018
  • First-Person Activity Forecasting with Online Inverse Reinforcement Learning [Paper] [Project]
    • N. Rhinehart, K. M. Kitani, ICCV 2017
  • Joint Prediction of Activity Labels and Starting Times in Untrimmed Videos [Paper]
    • T. Mahmud, M. Hasan, A. K. Roy-Chowdhury, ICCV 2017
  • Anticipating Daily Intention using On-Wrist Motion Triggered Sensing [Paper] [Project]
    • T. Y. Wu, T. A. Chien, C. S. Chan, C. W. Hu, M. Sun, ICCV 2017
  • Predicting Human Activities Using Stochastic Grammar [Paper] [Code]
    • S. Qi, S. Huang, P. Wei, S. C. Zhu, ICCV 2017
  • Using Cross-Model EgoSupervision to Learn Cooperative Basketball Intention [Paper]
    • G. Bertasius, J. Shi, ICCV 2017 Workshop
  • Long-Term Activity Forecasting using First-Person Vision [Paper]
    • S. Z. Bokhari, K. M. Kitani, ACCV 2016
  • Recurrent Neural Networks for Driver Activity Anticipation via Sensory-Fusion Architecture [Paper]
    • A. Jain, A. Singh, H. S. Koppula, S. Soh, A. Saxena, ICRA 2016

Event Prediction

  • Anticipating Traffic Accidents with Adaptive Loss and Large-scale Incident DB [Paper]
    • T. Suzuki, H. Kataoka, Y. Aoki, Y. Satoh, CVPR 2018
  • Agent-Centric Risk Assessment: Accident Anticipation and Risky Region Localization [Paper]
    • K. H. Zeng, S. H. Chou, F. H. Chan, J. C. Niebles, M. Sun, CVPR 2017
  • Anticipating accidents in dashcam videos [Paper] [Code] [Project]
    • F. H. Chan, Y. T. Chen, Y. Xiang, M. Sun, ACCV 2016
  • Car that Knows Before You Do: Anticipating Maneuvers via Learning Temporal Driving Models [Paper]
    • A. Jain, H. S. Koppula, B. Raghavan, S. Soh, A. Saxena, ICCV 2015

Human Trajectory Prediction

  • Looking to Relations for Future Trajectory Forecast [Paper]
    • C. Choi, B. Dariush, ICCV 2019
  • STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction [Paper]
    • Y. Huang, H. Bi, Z. Li, T. Mao, Z. Wang, ICCV 2019
  • Which Way Are You Going? Imitative Decision Learning for Path Forecasting in Dynamic Scenes [Paper]
    • Y. Li, CVPR 2019
  • SR-LSTM: State Refinement for LSTM Towards Pedestrian Trajectory Prediction [Paper]
    • P. Zhang, W. Ouyang, P. Zhang, J. Xue, N. Zheng, CVPR 2019
  • Multi-Agent Tensor Fusion for Contextual Trajectory Prediction [Paper]
    • T. Zhao, Y. Xu, M. Monfort, W. Choi, C. Baker, Y. Zhao, Y. Wang, Y. Nian Wu, CVPR 2019
  • Peeking into the Future: Predicting Future Person Activities and Locations in Videos [Paper]
    • J. Liang, L. Jiang, J.C. Niebles, A. Hauptmann, L. Fei-Fei, CVPR 2019
  • Sophie: An attentive gan for predicting paths compliant to social and physical constraints [Paper]
    • A. Sadeghian, V. Kosaraju, A. Sadeghian, N. Hirose, H. Rezatofighi, S. Savarese, CVPR 2019
  • Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty[Paper]
    • A. Bhattacharyya, M. Fritz, B. Schiele, CVPR 2018
  • Encoding Crowd Interaction with Deep Neural Network for Pedestrian Trajectory Prediction[Paper] [Code]
    • Y. Xu, Z. Piao, S. Gao, CVPR 2018
  • Human Trajectory Prediction using Spatially aware Deep Attention Models [Paper]
    • D. Varshneya, G. Srinivasaraghavan, arxiv 2017
  • Context-Aware Trajectory Prediction [Paper]
    • F. Bartoli, G. Lisanti, L. Ballan, A. D. Bimbo, arxiv 2017
  • Soft + Hardwired Attention: An LSTM Framework for Human Trajectory Prediction and Abnormal Event Detection [Paper]
    • T. Fernando, S. Denman, S. Sridharan, C. Fookes, arxiv 2017
  • Forecasting Interactive Dynamics of Pedestrians with Fictitious Play [Paper]
    • W. C. Ma, D. A. Huang, N. Lee, K. M. Kitani, CVPR 2017
  • Social LSTM: Human Trajectory Prediction in Crowded Spaces [Paper]
    • A. Alahi∗, K. Goel, V. Ramanathan, A. Robicquet, Li Fei-Fei, S. Savarese, *CVPR 2016**

Contributing

Feel free to send me email or Pull Request to add links.

Licenses

CC0

To the extent possible under law, Chin-An Cheng, Ching-Ju Cheng has waived all copyright and related or neighboring rights to this work.

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