Wang, J.Z.[Jin-Zhuo],
Wang, W.M.[Wen-Min],
Gao, W.[Wen],
Predicting Diverse Future Frames With Local Transformation-Guided
Masking,
CirSysVideo(29), No. 12, December 2019, pp. 3531-3543.
IEEE DOI
1912
Predictive models, Generators, Task analysis, Visualization,
Computational modeling, Complexity theory, Training,
video prediction on single frame
BibRef
Chen, X.Y.[Xin-Yuan],
Xu, C.[Chang],
Yang, X.K.[Xiao-Kang],
Tao, D.C.[Da-Cheng],
Long-Term Video Prediction via Criticization and Retrospection,
IP(29), 2020, pp. 7090-7103.
IEEE DOI
2007
Predictive models, Feature extraction, Training, Adaptive optics,
Optical imaging, Image reconstruction, Video prediction,
generative adversarial networks
BibRef
Chen, X.T.[Xiong-Tao],
Wang, W.M.[Wen-Min],
Uni-and-Bi-Directional Video Prediction via Learning Object-Centric
Transformation,
MultMed(22), No. 6, June 2020, pp. 1591-1604.
IEEE DOI
2005
Kernel, Predictive models, Task analysis, Bidirectional control,
Optical imaging, Image reconstruction, Visualization,
visual attention
BibRef
Lin, X.,
Zou, Q.,
Xu, X.,
Huang, Y.,
Tian, Y.,
Motion-Aware Feature Enhancement Network for Video Prediction,
CirSysVideo(31), No. 2, February 2021, pp. 688-700.
IEEE DOI
2102
Predictive models, Encoding, Multiprotocol label switching,
Stochastic processes, Dynamics, Feature extraction, Task analysis,
perceptual loss
BibRef
Choi, H.[Hyomin],
Bajic, I.V.[Ivan V.],
Affine Transformation-Based Deep Frame Prediction,
IP(30), 2021, pp. 3321-3334.
IEEE DOI
2103
Kernel, Predictive models, Image coding, Encoding,
Convolutional codes, Interpolation, Extrapolation,
affine transformation
BibRef
Kim, N.[Nayoung],
Kang, J.W.[Je-Won],
Dynamic Motion Estimation and Evolution Video Prediction Network,
MultMed(23), 2021, pp. 3986-3998.
IEEE DOI
2112
Kernel, Dynamics, Convolution, Streaming media, Motion estimation,
Adaptation models, Spatiotemporal phenomena,
Long Short-term Memory
BibRef
Kancharla, P.[Parimala],
Channappayya, S.S.[Sumohana S.],
Improving the Visual Quality of Video Frame Prediction Models Using
the Perceptual Straightening Hypothesis,
SPLetters(28), 2021, pp. 2167-2171.
IEEE DOI
2112
Predictive models, Computational modeling, Training,
Feature extraction, Visualization, Trajectory, Generators, video prediction
BibRef
Oprea, S.[Sergiu],
Martinez-Gonzalez, P.[Pablo],
Garcia-Garcia, A.[Alberto],
Castro-Vargas, J.A.[John Alejandro],
Orts-Escolano, S.[Sergio],
Garcia-Rodriguez, J.[Jose],
Argyros, A.A.[Antonis A.],
A Review on Deep Learning Techniques for Video Prediction,
PAMI(44), No. 6, June 2022, pp. 2806-2826.
IEEE DOI
2205
Survey, Video Prediction. Predictive models, Task analysis, Uncertainty, Deep learning,
Computational modeling, Video sequences, Training,
self-supervised learning
BibRef
Somraj, N.[Nagabhushan],
Kashi, M.S.[Manoj Surya],
Arun, S.P.,
Soundararajan, R.[Rajiv],
Understanding the perceived quality of video predictions,
SP:IC(102), 2022, pp. 116626.
Elsevier DOI
2202
Video quality assessment, Video prediction, Database,
Perceptual quality, Neural networks, Deep learning
BibRef
Liu, H.J.[Hao-Jie],
Lu, M.[Ming],
Chen, Z.Q.[Zhi-Qi],
Cao, X.[Xun],
Ma, Z.[Zhan],
Wang, Y.[Yao],
End-to-End Neural Video Coding Using a Compound Spatiotemporal
Representation,
CirSysVideo(32), No. 8, August 2022, pp. 5650-5662.
IEEE DOI
2208
Image coding, Spatiotemporal phenomena, Decoding,
Chemical reactors, Video coding, Feature extraction, Optical flow,
video prediction
BibRef
Kim, Y.G.[Young-Geun],
Lee, K.[Kyungbok],
Paik, M.C.[Myunghee Cho],
Conditional Wasserstein Generator,
PAMI(45), No. 6, June 2023, pp. 7208-7219.
IEEE DOI
2305
Generators, Data models, Linear programming, Task analysis,
Probability, Upper bound, Stochastic processes,
video prediction
BibRef
Chang, Z.[Zheng],
Zhang, X.F.[Xin-Feng],
Wang, S.S.[Shan-She],
Ma, S.W.[Si-Wei],
Gao, W.[Wen],
STAM: A SpatioTemporal Attention Based Memory for Video Prediction,
MultMed(25), 2023, pp. 2354-2367.
IEEE DOI
2306
Spatiotemporal phenomena, Predictive models, Visualization,
Logic gates, Feature extraction,
video prediction
BibRef
Li, P.[Ping],
Zhang, C.[Chenhan],
Xu, X.H.[Xiang-Hua],
Fast Fourier Inception Networks for Occluded Video Prediction,
MultMed(26), 2024, pp. 3418-3429.
IEEE DOI
2402
Dynamics, Convolutional codes, Task analysis, Spatiotemporal phenomena,
Predictive models, Streaming media, Fourier transform
BibRef
Lai, J.Y.[Jun-Yu],
Gan, L.Q.[Lian-Qiang],
Zhu, J.H.[Jun-Hong],
Liu, H.S.[Hua-Shuo],
Gao, L.L.[Lian-Li],
Exploring Spatial Frequency Information for Enhanced Video Prediction
Quality,
MultMed(26), 2024, pp. 8955-8968.
IEEE DOI
2408
Measurement, Predictive models, Feature extraction, Correlation,
Task analysis, Spatiotemporal phenomena, Video prediction, performance metric
BibRef
Davtyan, A.[Aram],
Sameni, S.[Sepehr],
Favaro, P.[Paolo],
Efficient Video Prediction via Sparsely Conditioned Flow Matching,
ICCV23(23206-23217)
IEEE DOI Code:
WWW Link.
2401
BibRef
Zhong, Y.Q.[Yi-Qi],
Liang, L.[Luming],
Zharkov, I.[Ilya],
Neumann, U.[Ulrich],
MMVP: Motion-Matrix-based Video Prediction,
ICCV23(4250-4260)
IEEE DOI
2401
BibRef
Villar-Corrales, A.[Angel],
Wahdan, I.[Ismail],
Behnke, S.[Sven],
Object-Centric Video Prediction Via Decoupling of Object Dynamics and
Interactions,
ICIP23(570-574)
IEEE DOI
2312
BibRef
Hu, X.T.[Xiao-Tao],
Huang, Z.W.[Zhe-Wei],
Huang, A.L.[Ai-Lin],
Xu, J.[Jun],
Zhou, S.C.[Shu-Chang],
A Dynamic Multi-Scale Voxel Flow Network for Video Prediction,
CVPR23(6121-6131)
IEEE DOI
2309
BibRef
Sun, M.Z.[Ming-Zhen],
Wang, W.N.[Wei-Ning],
Zhu, X.X.[Xin-Xin],
Liu, J.[Jing],
MOSO: Decomposing MOtion, Scene and Object for Video Prediction,
CVPR23(18727-18737)
IEEE DOI
2309
BibRef
Ye, X.[Xi],
Bilodeau, G.A.[Guillaume-Alexandre],
A unified model for continuous conditional video prediction,
Precognition23(3604-3613)
IEEE DOI
2309
BibRef
Ben Zikri, N.[Nir],
Sharf, A.[Andrei],
Phylonet: Physically-constrained Long-term Video Prediction,
ACCV22(VII:570-587).
Springer DOI
2307
BibRef
Wu, Y.[Yue],
Wen, Q.[Qiang],
Chen, Q.F.[Qi-Feng],
Optimizing Video Prediction via Video Frame Interpolation,
CVPR22(17793-17802)
IEEE DOI
2210
Training, Interpolation, Extrapolation, Computational modeling,
Semantics, Training data, Optimization methods,
Image and video synthesis and generation
BibRef
Jasti, R.[Rakesh],
Jampani, V.[Varun],
Sun, D.Q.[De-Qing],
Yang, M.H.[Ming-Hsuan],
Multi-Frame Video Prediction with Learnable Motion Encodings,
ICIP22(4198-4202)
IEEE DOI
2211
Deep learning, Knowledge engineering, Image coding,
Neural networks, Benchmark testing, Performance gain, Cameras
BibRef
Chang, Z.[Zheng],
Zhang, X.F.[Xin-Feng],
Wang, S.S.[Shan-She],
Ma, S.W.[Si-Wei],
Gao, W.[Wen],
STRPM: A Spatiotemporal Residual Predictive Model for High-Resolution
Video Prediction,
CVPR22(13926-13935)
IEEE DOI
2210
Predictive models, Feature extraction, Generative adversarial networks,
Spatiotemporal phenomena, Representation learning
BibRef
Geng, D.[Daniel],
Hamilton, M.[Max],
Owens, A.[Andrew],
Comparing Correspondences:
Video Prediction with Correspondence-wise Losses,
CVPR22(3355-3366)
IEEE DOI
2210
Interpolation, Visualization, Uncertainty, Prediction methods,
Position measurement,
Video analysis and understanding
BibRef
Gao, Z.Y.[Zhang-Yang],
Tan, C.[Cheng],
Wu, L.R.[Li-Rong],
Li, S.Z.[Stan Z.],
SimVP: Simpler yet Better Video Prediction,
CVPR22(3160-3170)
IEEE DOI
2210
Training, Costs, Recurrent neural networks, Computational modeling,
Predictive models,
Image and video synthesis and generation
BibRef
Tiwari, U.[Ujjwal],
Sreekar, P.A.[P. Aditya],
Namboodiri, A.[Anoop],
Cycle Consistency Based Method for Learning Disentangled Representation
for Stochastic Video Prediction,
CIAP22(III:265-277).
Springer DOI
2205
BibRef
Besbinar, B.[Beril],
Frossard, P.[Pascal],
Self-Supervision By Prediction for Object Discovery In Videos,
ICIP21(1509-1513)
IEEE DOI
2201
Deep learning, Annotations, Heuristic algorithms, Pipelines,
Dynamics, Predictive models, Self-supervision, video prediction,
unsupervised scene decomposition
BibRef
Chatterjee, M.[Moitreya],
Ahuja, N.[Narendra],
Cherian, A.[Anoop],
A Hierarchical Variational Neural Uncertainty Model for Stochastic
Video Prediction,
ICCV21(9731-9741)
IEEE DOI
2203
Training, Measurement, Deep learning, Uncertainty, Graphical models,
Stochastic processes, Representation learning
BibRef
Wu, B.[Bohan],
Nair, S.[Suraj],
Martín-Martín, R.[Roberto],
Fei-Fei, L.[Li],
Finn, C.[Chelsea],
Greedy Hierarchical Variational Autoencoders for Large-Scale Video
Prediction,
CVPR21(2318-2328)
IEEE DOI
2111
Training, Visualization, Memory management, Stacking,
Predictive models, Planning
BibRef
Liu, B.[Bowen],
Chen, Y.[Yu],
Liu, S.Y.[Shi-Yu],
Kim, H.S.[Hun-Seok],
Deep Learning in Latent Space for Video Prediction and Compression,
CVPR21(701-710)
IEEE DOI
2111
Deep learning, Redundancy, Video sequences, Rate-distortion,
Transforms, Video compression, Generative adversarial networks
BibRef
Bei, X.Z.[Xin-Zhu],
Yang, Y.C.[Yan-Chao],
Soatto, S.[Stefano],
Learning Semantic-Aware Dynamics for Video Prediction,
CVPR21(902-912)
IEEE DOI
2111
Training, Layout, Semantics, Dynamics,
Predictive models
BibRef
Razali, H.[Haziq],
Fernando, B.[Basura],
A Log-likelihood Regularized KL Divergence for Video Prediction With
a 3D Convolutional Variational Recurrent Network,
WACVW21(209-217) Generation of Human Behavior
IEEE DOI
2105
Solid modeling, Stochastic processes, Predictive models, Tools
BibRef
Seo, Y.G.[Young-Gyo],
Lee, K.[Kimin],
Liu, F.C.[Fang-Chen],
James, S.[Stephen],
Abbeel, P.[Pieter],
HARP: Autoregressive Latent Video Prediction with High-Fidelity Image
Generator,
ICIP22(3943-3947)
IEEE DOI
2211
Predictive models, Benchmark testing, Transformers, Generators,
Data models, Task analysis, Video Prediction, Transformer
BibRef
Wu, H.X.[Hai-Xu],
Yao, Z.Y.[Zhi-Yu],
Wang, J.M.[Jian-Min],
Long, M.S.[Ming-Sheng],
MotionRNN: A Flexible Model for Video Prediction with
Spacetime-Varying Motions,
CVPR21(15430-15439)
IEEE DOI
2111
Road transportation, Adaptation models,
Predictive models,
Spatiotemporal phenomena
BibRef
Lee, S.M.[Sang-Min],
Kim, H.G.[Hak Gu],
Choi, D.H.[Dae Hwi],
Kim, H.I.[Hyung-Il],
Ro, Y.M.[Yong Man],
Video Prediction Recalling Long-term Motion Context via Memory
Alignment Learning,
CVPR21(3053-3062)
IEEE DOI
2111
Legged locomotion, Codes, Impedance matching,
Dynamics, Training data
BibRef
Wang, Y.,
Wu, J.,
Long, M.,
Tenenbaum, J.B.,
Probabilistic Video Prediction From Noisy Data With a Posterior
Confidence,
CVPR20(10827-10836)
IEEE DOI
2008
Predictive models, Uncertainty, Bayes methods, Noise measurement,
Mathematical model, Streaming media, Stochastic processes
BibRef
Le Guen, V.,
Thome, N.,
Disentangling Physical Dynamics From Unknown Factors for Unsupervised
Video Prediction,
CVPR20(11471-11481)
IEEE DOI
2008
Predictive models, Forecasting, Mathematical model,
Computer architecture, Computational modeling, Training,
Recurrent neural networks
BibRef
Jin, B.B.[Bei-Bei],
Hu, Y.[Yu],
Tang, Q.K.[Qian-Kun],
Niu, J.Y.[Jing-Yu],
Shi, Z.P.[Zhi-Ping],
Han, Y.H.[Yin-He],
Li, X.W.[Xiao-Wei],
Exploring Spatial-Temporal Multi-Frequency Analysis for High-Fidelity
and Temporal-Consistency Video Prediction,
CVPR20(4553-4562)
IEEE DOI
2008
Discrete wavelet transforms, Predictive models, Wavelet analysis,
Streaming media, Time-frequency analysis
BibRef
Ho, Y.H.,
Chan, C.C.,
Peng, W.H.,
Deep Video Prediction Through Sparse Motion Regularization,
ICIP20(1646-1650)
IEEE DOI
2011
Predictive models, Adaptive optics, Training, Optical sensors,
Optical losses, Integrated optics, Optical imaging,
weighted K-means
BibRef
Ho, Y.,
Chan, C.,
Alexandre, D.,
Peng, W.,
Chang, C.,
P-frame Coding Proposal by NCTU: Parametric Video Prediction through
Backprop-based Motion Estimation,
CLIC20(598-601)
IEEE DOI
2008
Encoding, Image coding, Motion estimation, Nonlinear optics,
Optical imaging, Decoding, Optical buffering
BibRef
Ho, Y.H.[Yung-Han],
Cho, C.Y.[Chuan-Yuan],
Peng, W.H.[Wen-Hsiao],
Deep Reinforcement Learning for Video Prediction,
ICIP19(604-608)
IEEE DOI
1910
Reinforcement learning, deep video prediction
BibRef
Ho, Y.,
Cho, C.,
Jin, G.,
Peng, W.,
SME-Net: Sparse Motion Estimation for Parametric Video Prediction
Through Reinforcement Learning,
ICCV19(10461-10469)
IEEE DOI
2004
data compression, image sequences,
learning (artificial intelligence), motion compensation,
BibRef
Hu, Z.,
Wang, J.,
A Novel Adversarial Inference Framework for Video Prediction with
Action Control,
SDL-CV19(768-772)
IEEE DOI
2004
image motion analysis, image representation,
image segmentation, image sequences, neural nets, Cycle Consistent
BibRef
Zhu, D.Y.[De-Yao],
Munderloh, M.[Marco],
Rosenhahn, B.[Bodo],
Stückler, J.[Jörg],
Learning to Disentangle Latent Physical Factors for Video Prediction,
GCPR19(595-608).
Springer DOI
1911
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Image Manipulation -- Sampling, Reduction, Decimation, General Size Changes, Resizing .