Paper Overview


Paper Title
Action recognition by Latent Duration Model [Tingwei Wang, Chuancai Liu and Liantao Wang]new
Adding Attentiveness to the Neurons in Recurrent Neural Networks [Pengfei Zhang, Jianru Xue, Cuiling Lan, Wenjun Zeng, Zhanning Gao, Nanning Zheng]new
Learning and Using the Arrow of Time [Donglai Wei, Jospeh Lim, Andrew Zisserman, William T. Freeman]new
End-to-End Learning of Motion Representation for Video Understanding [Lijie Fan, Wenbing Huang, Chuang Gan, Stefano Ermon, Boqing Gong, Junzhou Huang]new
Making Convolutional Networks Recurrent for Visual Sequence Learning [Xiaodong Yang, Pavlo Molchanov, Jan Kautz]new
Learning Latent Super-Events to Detect Multiple Activities in Videos [AJ Piergiovanni, Michael S. Ryoo]new
Geometry Guided Convolutional Neural Networks for Self-Supervised Video Representation Learning [Chuang Gan, Boqing Gong, Kun Liu, Hao Su, Leonidas J. Guibas]new
Recognize Actions by Disentangling Components of Dynamics [Yue Zhao, Yuanjun Xiong, Dahua Lin]new
Weakly-Supervised Action Segmentation with Iterative Soft Boundary Assignment [Li Ding, Chenliang Xu]new
Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognition [Shuyang Sun, Zhanghui Kuang, Wanli Ouyang, Lu Sheng, Wei Zhang]new
MiCT: Mixed 3D/2D Convolutional Tube for Human Action Recognition [Yizhou Zhou, Xiaoyan Sun, Zheng-Jun Zha, Wenjun Zeng]new
Non-Linear Temporal Subspace Representations for Activity Recognition [Anoop Cherian, Suvrit Sra, Stephen Gould, Richard Hartley]new
Video Representation Learning Using Discriminative Pooling [Jue Wang, Anoop Cherian, Fatih Porikli, Stephen Gould]new
PoTion: Pose MoTion Representation for Action Recognition [Vasileios Choutas, Philippe Weinzaepfel, Jérôme Revaud, Cordelia Schmid]new
Activity Recognition based on a Magnitude-Orientation Stream Network [Caetano, C., de Melo, V. H. C., dos Santos, J. A., Schwartz, W. R.]new
What Makes a Video a Video: Analyzing Temporal Information in Video Understanding Models and Datasets [De-An Huang, Vignesh Ramanathan, Dhruv Mahajan, Lorenzo Torresani , Manohar Paluri, Li Fei-Fei, and Juan Carlos Niebles]new
What Makes a Video a Video: Analyzing Temporal Information in Video Understanding Models and Datasets [De-An Huang, Vignesh Ramanathan, Dhruv Mahajan, Lorenzo Torresani , Manohar Paluri, Li Fei-Fei, and Juan Carlos Niebles]new
A Closer Look at Spatiotemporal Convolutions for Action Recognition [Du Tran , Heng Wang , Lorenzo Torresani , Jamie Ray, Yann LeCun, Manohar Paluri]new
Making Convolutional Networks Recurrent for Visual Sequence Learning [Xiaodong Yang, Pavlo Molchanov, Jan Kautz ]new
Temporal Dynamic Graph LSTM for Action-driven Video Object Detection [Yuan Yuan, Xiaodan Liang, Xiaolong Wang, Dit-Yan Yeung, Abhinav Gupta]new
Compressed Video Action Recognition [Chao-Yuan Wu and Manzil Zaheer and Hexiang Hu and R. Manmatha and Alexander J. Smola and Philipp Kraehenbuehl]new
An End-to-end 3D Convolutional Neural Network for Action Detection and Segmentation in Videos [Rui Hou and Chen Chen and Mubarak Shah]new
Action Recognition Using Super Sparse Coding Vector with Spatio-Temporal Awareness [Xiaodong Yang, Ying-Li Tian]new
Multilayer and Multimodal Fusion of Deep Neural Networks for Video Classification [Xiaodong Yang, Pavlo Molchanov, Jan Kautz]new
Multilayer and Multimodal Fusion of Deep Neural Networks for Video Classification [Xiaodong Yang, Pavlo Molchanov, Jan Kautz]new
Non-local Neural Networks [Xiaolong Wang, Ross Girshick, Abhinav Gupta, Kaiming He]new
Temporal 3D ConvNets: New Architecture and Transfer Learning for Video Classification [Ali Diba, Mohsen Fayyaz, Vivek Sharma, Amir Hossein Karami, Mohammad Mahdi Arzani, Rahman Yousefzadeh, Luc Van Gool]new
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]new
Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion [Weiyao Lin , Yang Mi , Jianxin Wu , Ke Lu , Hongkai Xiong]new
Appearance-and-Relation Networks for Video Classification [Limin Wang , Wei Li , Wen Li ,Luc Van Gool]new
Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification [Xiang Long , Chuang Gan , Gerard de Melo , Jiajun Wu , Xiao Liu , Shilei Wen]new
Can Spatiotemporal 3D CNNs Retrace the History of 2D CNNs and ImageNet? [Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh]new
Learning Spatio-Temporal Features with 3D Residual Networks for Action Recognition [Kensho Hara, Hirokatsu Kataoka, Yutaka Satoh]new
Action Recognition with Coarse-to-Fine Deep Feature Integration and Asynchronous Fusion [Weiyao Lin, Yang Mi, Jianxin Wu, Ke Lu, Hongkai Xiong]new
End-to-end Video-level Representation Learning for Action Recognition [Jiagang Zhu, Wei Zou, Zheng Zhu, Lin Li]new
Chained Multi-stream Networks Exploiting Pose, Motion, and Appearance for Action Classification and Detection [Mohammadreza Zolfaghari , Gabriel L. Oliveira, Nima Sedaghat, Thomas Brox]new
Lattice Long Short-Term Memory for Human Action Recognition [Lin Sun, Kui Jia, Kevin Chen, Dit Yan Yeung, Bertram E. Shi, Silvio Savarese]new
ActionVLAD: Learning spatio-temporal aggregation for action classification [Rohit Girdhar, Deva Ramanan, Abhinav Gupta, Josef Sivic, Bryan Russell]new
Asynchronous Temporal Fields for Action Recognition [Gunnar A. Sigurdsson, Santosh Divvala, Ali Farhadi, Abhinav Gupta]new
Predictive-Corrective Networks for Action Detection [Achal Dave,Olga Russakovsky,Deva Ramanan]new
R-C3D: Region Convolutional 3D Network for Temporal Activity Detection [Huijuan Xu,Abir Das,Kate Saenko]new
Pillar Networks++: Distributed non-parametric deep and wide networks [Biswa Sengupta, Yu Qian]new
Eigen Evolution Pooling for Human Action Recognition [Yang Wang, Vinh Tran, Minh Hoai]new
Learning Long-Term Dependencies for Action Recognition With a Biologically-Inspired Deep Network [Yemin Shi, Yonghong Tian, Yaowei Wang, Wei Zeng, Tiejun Huang]new
AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions [Chunhui Gu, Chen Sun, Sudheendra Vijayanarasimhan, Caroline Pantofaru, David A. Ross, George Toderici, Yeqing Li, Susanna Ricco, Rahul Sukthankar, Cordelia Schmid, Jitendra Malik]new
Multi-Label Zero-Shot Human Action Recognition via Joint Latent Embedding [Qian Wang, Ke Chen]new
Recurrent Assistance: Cross-Dataset Training of LSTMs on Kitchen Tasks [Toby Perrett Dima Damen]new
Learning Gating ConvNet for Two-Stream based Methods in Action Recognition [Jiagang Zhu , Wei Zou , Zheng Zhu]new
Improved Rank Pooling Strategy for Complex Action Recognition [Eman Mohammadi, Q. M. Jonathan Wu, Mehrdad Saif]new
Video Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor [Aaron Chadha, Alhabib Abbas and Yiannis Andreopoulos]new
Robust Action Recognition framework using Segmented Block and Distance Mean Histogram of Gradients Approach [Vikas Tripathi, Durgaprasad Gangodkar, Ankush Mittal, Vishnu Kanth]new
Asynchronous Temporal Fields for Action Recognition [Gunnar A. Sigurdsson, Santosh Divvala, Ali Farhadi, Abhinav Gupta]new
Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding [Gunnar A. Sigurdsson and G{"u}l Varol and Xiaolong Wang and Ali Farhadi and Ivan Laptev and Abhinav Gupta]new
Pillar Networks++: Distributed non-parametric deep and wide networks [Biswa Sengupta, Yu Qian]new
Pillar Networks for action recognition [Biswa Sengupta, Yu Qian]new
Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset [Joao Carreira, Andrew Zisserman]new
Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition [ An-An Liu, Yu-Ting Su, Wei-Zhi Nie, Mohan Kankanhalli]new
Higher-order Pooling of CNN Features via Kernel Linearization for Action Recognition [A. Cherian, P. Koniusz, S. Gould]new
Action Recognition with Stacked Fisher Vectors [Xiaojiang Peng, Changqing Zou, Yu Qiao, Qiang Peng]new
P-CNN: Pose-based CNN Features for Action Recognition [Guilhem Cheron, Ivan Laptev, Cordelia Schmid]new
Spatiotemporal Multiplier Networks for Video Action Recognition [Christoph Feichtenhofer, Axel Pinz, Richard P. Wildes]new
The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities [H. Kuehne, A. B. Arslan and T. Serre]new
Weakly Supervised Action Learning with RNN based Fine-to-coarse Modeling [Alexander Richard, Hilde Kuehne, Juergen Gall]new
An end-to-end generative framework for video segmentation and recognition [Hilde Kuehne, Juergen Gall, Thomas Serre]new
Finding Action Tubes [Georgia Gkioxari, Jitendra Malik]new
Multi-region two-stream R-CNN for action detection [Xiaojiang Peng, Cordelia Schmid]new
Weakly supervised learning of actions from transcripts [Hilde Kuehne, Alexander Richard, Juergen Gall]new
Spatiotemporal Pyramid Network for Video Action Recognition [Yunbo Wang, Mingsheng Long, Jianmin Wang, Philip S. Yu]new
Action Representation Using Classifier Decision Boundarie s [Yi Zhu, Zhenzhong Lan, Shawn Newsam, Alexander G. Hauptmann]new
Generalized Rank Pooling for Activity Recognition [Anoop Cherian, Basura Fernando, Mehrtash Harandi, Stephen Gould]new
Connectionist temporal modeling for weakly supervised action labeling [D.-A. Huang, L. Fei-Fei, and J. C. Niebles]new
Weakly supervised learning of actions from transcripts. [H. Kuehne, A. Richard, and J. Gall]new
Weakly supervised action labeling in videos under ordering constraints [P. Bojanowski, R. Lajugie, F. Bach, I. Laptev, J. Ponce, C. Schmid, and J. Sivic]new
Weakly Supervised Action Labeling in Videos Under Ordering Constraints [Bojanowski, Piotr and Lajugie, R'emi and Bach, Francis and Laptev, Ivan and Ponce, Jean and Schmid, Cordelia and Sivic, Josef]new
Towards understanding action recognition [H. Jhuang and J. Gall and S. Zuffi and C. Schmid and M. J. Black]new
The Language of Actions: Recovering the Syntax and Semantics of Goal-Directed Human Activities [H. Kuehne, A. B. Arslan and T. Serre]new
ActionVLAD: Learning spatio-temporal aggregation for action classification [Rohit Girdhar, Deva Ramanan, Abhinav Gupta, Josef Sivic, Bryan Russell]new
Action Representation Using Classifier Decision Boundaries [Jue Wang , Anoop Cherian , Fatih Porikli , Stephen Gould]new
Hidden Two-Stream Convolutional Networks for Action Recognition [Yi Zhu , Zhenzhong Lan ,Shawn Newsam ,Alexander G. Hauptmann ]new
Learning spatiotemporal features with 3d convolutional networks [Tran, D., Bourdev, L.D., Fergus, R., Torresani, L., Paluri, M]new
Action recognition with improved trajectories [Wang, H., Schmid, C]new
Beyond short snippets: Deep networks for video classification [Ng, J.Y.H., Hausknecht, M., Vijayanarasimhan, S., Vinyals, O., Monga, R., Toderici, G]new
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition [Limin Wang , Yuanjun Xiong , Zhe Wang , Yu Qiao , Dahua Lin , Xiaoou Tang , and Luc Van Gool]new
A key volume mining deep framework for action recognition [Zhu, W., Hu, J., Sun, G., Cao, X., Qiao, Y]new
Long-term temporal convolutions for action recognition [Varol, G., Laptev, I., Schmid, C]new
Action recognition with trajectory-pooled deepconvolutional descriptors [Wang, L., Qiao, Y., Tang, X]new
Human action recognition using factorized spatio-temporal convolutional networks [Sun, L., Jia, K., Yeung, D., Shi, B.E]new
Motion part regularization: Improving action recognition via trajectory group selection [Ni, B., Moulin, P., Yang, X., Yan, S]new
Modeling video evolution for action recognition [Fernando, B., Gavves, E., M., J.O., Ghodrati, A.]new
Two-stream convolutional networks for action recognition in videos [Simonyan, K., Zisserman, A]new
A multi-level representation for action recognition [Wang, L., Qiao, Y., Tang, X]new
Bag of visual words and fusion methods for action recognition: Comprehensive study and good practice [Peng, X., Wang, L., Wang, X., Qiao, Y]new
Multi-view super vector for action recognition [Cai, Z., Wang, L., Peng, X., Qiao, Y]new