19.4.3.16.2 Video Frame Interpolation -- Interpolation Operations

Chapter Contents (Back)
Interpolation. Video Interpolation. Frame Interpolation. The related:
See also Video Super-Resolution, Resolution Enhancement.

Fogel, S.[Sergei],
Segmentation-based method for motion-compensated frame interpolation,
US_Patent6,008,865, Dec 28, 1999
WWW Link. BibRef 9912

Aguado, A.S.[Alberto S.], Montiel, E.[Eugenia],
Progressive Linear Search for Stereo Matching and Its Application to Interframe Interpolation,
CVIU(81), No. 1, January 2001, pp. 46-71.
DOI Link 0102
BibRef

Liu, T.Y.[Tie-Yan], Lo, K.T.[Kwok-Tung], Feng, J.[Jian], Zhang, X.D.[Xu-Dong],
Frame interpolation scheme using inertia motion prediction,
SP:IC(18), No. 3, March 2003, pp. 221-229.
Elsevier DOI 0304
BibRef

Liu, S.[Shan], Kuo, C.C.J.[C.C. Jay], Kim, J.W.[Jong-Won],
Hybrid global-local motion compensated frame interpolation for low bit rate video coding,
JVCIR(14), No. 1, March 2002, pp. 58-76.
Elsevier DOI 0304
BibRef

Huang, A.M.[Ai-Mei], Nguyen, T.Q.[Truong Q.],
A Multistage Motion Vector Processing Method for Motion-Compensated Frame Interpolation,
IP(17), No. 5, May 2008, pp. 694-708.
IEEE DOI 0804
BibRef
Earlier:
A Novel Multi-Stage Motion Vector Processing Method for Motion Compensated Frame Interpolation,
ICIP07(V: 389-392).
IEEE DOI 0709
BibRef
Earlier:
Motion Vector Processing Based on Residual Energy Information for Motion Compensated Frame Interpolation,
ICIP06(2721-2724).
IEEE DOI 0610
BibRef

Huang, A.M.[Ai-Mei], Nguyen, T.Q.[Truong Q.],
Motion vector processing using the color information,
ICIP09(1605-1608).
IEEE DOI 0911
BibRef

Huang, A.M.[Ai-Mei], Nguyen, T.Q.[Truong Q.],
Correlation-Based Motion Vector Processing With Adaptive Interpolation Scheme for Motion-Compensated Frame Interpolation,
IP(18), No. 4, April 2009, pp. 740-752.
IEEE DOI 0903
BibRef
Earlier:
Correlation-based motion vector processing for motion compensated frame interpolation,
ICIP08(1244-1247).
IEEE DOI 0810
BibRef

Huang, A.M.[Ai-Mei], Nguyen, T.Q.[Truong Q.],
Motion vector processing based on trajectory curve analysis for motion compensated frame interpolation,
ICIP09(377-380).
IEEE DOI 0911
BibRef

Choi, B.D.[Byeong-Doo], Han, J.W.[Jong-Woo], Kim, C.S.[Chang-Su], Ko, S.J.[Sung-Jea],
Motion-Compensated Frame Interpolation Using Bilateral Motion Estimation and Adaptive Overlapped Block Motion Compensation,
CirSysVideo(17), No. 4, April 2007, pp. 407-416.
IEEE DOI 0705
BibRef

Lee, S.H.[Sang-Heon], Lee, H.J.[Hyuk-Jae],
Motion-Compensated Frame Interpolation for Intra-Mode Blocks,
IEICE(E91-D), No. 4, April 2008, pp. 1117-1126.
DOI Link 0804
BibRef

Lee, S.H.[Sang Heon], Lee, S.H.[Sang Hwa], Yang, J.H.[Jeong Hyu], Cho, N.I.[Nam Ik],
A motion vector prediction method for multi-view video coding,
JVCIR(21), No. 7, October 2010, pp. 677-681.
Elsevier DOI 1003
Multi-view video coding, Motion vector prediction, Disparity vector prediction, Inter-view prediction, JMVM, View-temporal prediction; Probability of inter-view prediction, Magnitude of MV prediction residual BibRef

Lee, S.H.[Sang Heon], Lee, S.H.[Sang Hwa], Cho, N.I.[Nam Ik],
Hybrid Resolution Switching Method for Low Bit Rate Video Coding,
ICIP07(VI: 73-76).
IEEE DOI 0709
BibRef

Dikbas, S., Altunbasak, Y.,
Novel True-Motion Estimation Algorithm and Its Application to Motion-Compensated Temporal Frame Interpolation,
IP(22), No. 8, 2013, pp. 2931-2945.
IEEE DOI 1307
interpolation, block-matching algorithm, Frame interpolation; BibRef

Lim, H., Park, H.W.,
A Symmetric Motion Estimation Method for Motion-Compensated Frame Interpolation,
IP(20), No. 12, December 2011, pp. 3653-3658.
IEEE DOI 1112
BibRef

Kim, J.S.[Joon-Seek], Park, R.H.[Rae-Hong],
Local motion-adaptive interpolation technique based on block matching algorithms,
SP:IC(4), No. 6, November 1992, pp. 519-528.
Elsevier DOI 0001
Block matching algorithm, frame interpolation, integral projections; motion vector, motion vector correction, region segmentation, PSNR BibRef

Lim, H., Park, H.W.,
A Region-Based Motion-Compensated Frame Interpolation Method Using a Variance-Distortion Curve,
CirSysVideo(25), No. 3, March 2015, pp. 518-524.
IEEE DOI 1503
Interpolation BibRef

Kim, D., Lim, H., Park, H.W.,
Iterative True Motion Estimation for Motion-Compensated Frame Interpolation,
CirSysVideo(23), No. 3, March 2013, pp. 445-454.
IEEE DOI 1303
BibRef

Jeon, D.S.[Dong-San], Park, H.W.[Hyun-Wook],
An adaptive reference frame selection method for multiple reference frame motion estimation in the H.264/AVC,
ICIP09(629-632).
IEEE DOI 0911
BibRef

Park, J.H.[Ju Hyun], Kim, Y.C.[Young-Chul], Hoon, H.S.[Hong-Sung],
Edge-Based Motion Vector Processing for Frame Interpolation Based on Weighted Vector Median Filter,
IEICE(E93-D), No. 11, November 2010, pp. 3132-3135.
WWW Link. 1011
BibRef

Jeong, S.G.[Seong-Gyun], Lee, C.[Chul], Kim, C.S.[Chang-Su],
Motion-Compensated Frame Interpolation Based on Multihypothesis Motion Estimation and Texture Optimization,
IP(22), No. 11, 2013, pp. 4497-4509.
IEEE DOI 1310
interpolation BibRef

Yu, Z.F.[Zhe-Fei], Li, H.Q.[Hou-Qiang], Wang, Z.Y.[Zhang-Yang], Hu, Z.[Zeng], Chen, C.W.[Chang Wen],
Multi-Level Video Frame Interpolation: Exploiting the Interaction Among Different Levels,
CirSysVideo(23), No. 7, 2013, pp. 1235-1248.
IEEE DOI 1307
interpolation BibRef

Cho, Y.H.[Yang-Ho], Lee, H.Y.[Ho-Yeong], Park, D.S.[Du-Sik],
Temporal Frame Interpolation Based on Multiframe Feature Trajectory,
CirSysVideo(23), No. 12, 2013, pp. 2105-2115.
IEEE DOI 1312
Feature extraction BibRef

Cho, Y.H.[Yang-Ho], Lee, H.Y.[Ho-Yeong], Park, D.S.[Du-Sik], Kim, C.Y.[Chang-Yeong],
Enhancement for temporal resolution of video based on multi-frame feature trajectory and occlusion compensation,
ICIP09(389-392).
IEEE DOI 0911

See also Temporal and inter-view skip modes for multi-view video coding. BibRef

Heinz, F.[Florian], Güting, R.H.[Ralf Hartmut],
Robust high-quality interpolation of regions to moving regions,
GeoInfo(20), No. 3, July 2016, pp. 385-413.
Springer DOI 1605
For a region over a time interval. BibRef

Zhang, Y., Xu, L., Ji, X., Dai, Q.,
A Polynomial Approximation Motion Estimation Model for Motion-Compensated Frame Interpolation,
CirSysVideo(26), No. 8, August 2016, pp. 1421-1432.
IEEE DOI 1609
image texture BibRef

Li, R.[Ran], Liu, H.B.[Hong-Bing], Liu, Z.H.[Zheng-Hui], Li, Y.L.[Yan-Ling], Fu, Z.J.[Zhang-Jie],
Motion-compensated frame interpolation using patch-based sparseland model,
SP:IC(54), No. 1, 2017, pp. 36-48.
Elsevier DOI 1704
Motion-compensated frame interpolation BibRef

Liu, H.B.[Hong-Bin], Xiong, R.Q.[Rui-Qin], Ma, S.W.[Si-Wei], Zhao, D.B.[De-Bin], Gao, W.[Wen],
Bayesian frame interpolation by fusing multiple motion-compensated prediction frames,
ICIP11(1173-1176).
IEEE DOI 1201
BibRef

Liu, J.Y.[Jia-Ying], Xia, S.F.[Si-Feng], Yang, W.H.[Wen-Han], Li, M.D.[Ma-Ding], Liu, D.[Dong],
One-for-All: Grouped Variation Network-Based Fractional Interpolation in Video Coding,
IP(28), No. 5, May 2019, pp. 2140-2151.
IEEE DOI 1903
convolutional neural nets, image filtering, image restoration, image sequences, interpolation, grouped variation network BibRef

Choi, G., Heo, P., Park, H.,
Triple-Frame-Based Bi-Directional Motion Estimation for Motion-Compensated Frame Interpolation,
CirSysVideo(29), No. 5, May 2019, pp. 1251-1258.
IEEE DOI 1905
Bidirectional control, Reliability, Motion estimation, Interpolation, Filtering, Tracking, Time complexity, motion vector refinement BibRef

Choi, G., Heo, P., Oh, S.R., Park, H.,
A new motion estimation method for motion-compensated frame interpolation using a convolutional neural network,
ICIP17(800-804)
IEEE DOI 1803
Acoustics, Indexes, Speech, Speech processing, Motion estimation, frame rate up-conversion, neural networks BibRef

Ding, X., Zhu, N., Li, L., Li, Y., Yang, G.,
Robust Localization of Interpolated Frames by Motion-Compensated Frame Interpolation Based on an Artifact Indicated Map and Tchebichef Moments,
CirSysVideo(29), No. 7, July 2019, pp. 1893-1906.
IEEE DOI 1907
Interpolation, Forensics, Forgery, Robustness, Detectors, Shape, Feature extraction, Video forensics, Tchebichef moments BibRef

Zhang, T.[Tao], Jiang, P.P.[Pei-Pei], Zhang, M.[Meng],
Inter-frame video image generation based on spatial continuity generative adversarial networks,
SIViP(13), No. 8, November 2019, pp. 1487-1494.
WWW Link. 1911
BibRef

Paliwal, A.[Avinash], Kalantari, N.K.[Nima Khademi],
Deep Slow Motion Video Reconstruction With Hybrid Imaging System,
PAMI(42), No. 7, July 2020, pp. 1557-1569.
IEEE DOI 2006
Spatial resolution, Cameras, Streaming media, Image reconstruction, Interpolation, Estimation, Computational photography, hybrid imaging BibRef

Kalantari, N.K., Shechtman, E., Darabi, S., Goldman, D.B., Sen, P.,
Improving patch-based synthesis by learning patch masks,
ICCP14(1-8)
IEEE DOI 1411
feature extraction. For hole-filling, retargeting, and reshuffling. BibRef

Kokaram, A.[Anil], Singh, D.[Davinder], Robinson, S.[Simon], Kelly, D.[Damien], Collis, B.[Bill], Libreri, K.[Kim],
Motion-based frame interpolation for film and television effects,
IET-CV(14), No. 6, September 2020, pp. 323-338.
DOI Link 2010
BibRef

Yang, Y.[Yoonmo], Oh, B.T.[Byung Tae],
Video frame interpolation using deep cascaded network structure,
SP:IC(89), 2020, pp. 115982.
Elsevier DOI 2010
Frame interpolation, Frame-rate up-conversion, Deep learning, Convolutional neural network (CNN) BibRef

Cheng, X., Chen, Z.,
A Multi-Scale Position Feature Transform Network for Video Frame Interpolation,
CirSysVideo(30), No. 11, November 2020, pp. 3968-3981.
IEEE DOI 2011
Interpolation, Transforms, Optical sensors, Optical imaging, Neural networks, Optical computing, Optical fiber networks, multi-scale network BibRef

Shen, W., Bao, W., Zhai, G., Chen, L., Min, X., Gao, Z.,
Video Frame Interpolation and Enhancement via Pyramid Recurrent Framework,
IP(30), 2021, pp. 277-292.
IEEE DOI 2011
Video frame interpolation, spatial degradation, video deblurring, video super-resolution, neural network BibRef

Jin, X.[Xing], Tang, P.[Ping], Houet, T.[Thomas], Corpetti, T.[Thomas], Alvarez-Vanhard, E.G.[Emilien Gence], Zhang, Z.[Zheng],
Sequence Image Interpolation via Separable Convolution Network,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Bao, W.B.[Wen-Bo], Lai, W.S.[Wei-Sheng], Zhang, X.Y.[Xiao-Yun], Gao, Z.Y.[Zhi-Yong], Yang, M.H.[Ming-Hsuan],
MEMC-Net: Motion Estimation and Motion Compensation Driven Neural Network for Video Interpolation and Enhancement,
PAMI(43), No. 3, March 2021, pp. 933-948.
IEEE DOI 2102
Interpolation, Kernel, Estimation, Motion estimation, Adaptation models, Optical imaging, Motion compensation, adaptive warping BibRef

Park, M., Kim, H.G., Lee, S., Ro, Y.M.,
Robust Video Frame Interpolation With Exceptional Motion Map,
CirSysVideo(31), No. 2, February 2021, pp. 754-764.
IEEE DOI 2102
Interpolation, Optical imaging, Streaming media, Motion detection, Nonlinear optics, Optical computing, Deep learning, exceptional motion estimation BibRef

Zhang, D.C.[Da-Cheng], Lei, W.M.[Wei-Min], Zhang, W.[Wei], Chen, X.Y.[Xin-Yi],
Flow-based frame interpolation networks combined with occlusion-aware mask estimation,
IET-IPR(14), No. 17, 24 December 2020, pp. 4579-4587.
DOI Link 2104
BibRef

Kuznetsova, A.[Alina], Talati, A.[Aakrati], Luo, Y.[Yiwen], Simmons, K.[Keith], Ferrari, V.[Vittorio],
Efficient video annotation with visual interpolation and frame selection guidance,
WACV21(3069-3078)
IEEE DOI 2106
Interpolation, Visualization, Extrapolation, Annotations, Image annotation BibRef

Yu, L.W.[Liang-Wei], Shen, L.Q.[Li-Quan], Yang, H.[Hao], Jiang, X.[Xuhao], Yan, B.[Bo],
A Distortion-Aware Multi-Task Learning Framework for Fractional Interpolation in Video Coding,
CirSysVideo(31), No. 7, July 2021, pp. 2824-2836.
IEEE DOI 2107
Interpolation, Distortion, Feature extraction, Video coding, Training, Task analysis, Image coding, Fractional interpolation, multi-task learning BibRef

Liu, C.X.[Cheng-Xu], Yang, H.[Huan], Fu, J.L.[Jian-Long], Qian, X.M.[Xue-Ming],
TTVFI: Learning Trajectory-Aware Transformer for Video Frame Interpolation,
IP(32), 2023, pp. 4728-4741.
IEEE DOI 2309
BibRef
Earlier:
Learning Trajectory-Aware Transformer for Video Super-Resolution,
CVPR22(5677-5686)
IEEE DOI 2210
Visualization, Computational modeling, Superresolution, Video sequences, Transformers, Tokenization, Trajectory, Low-level vision BibRef

Qiu, Z.W.[Zhong-Wei], Yang, H.[Huan], Fu, J.L.[Jian-Long], Liu, D.C.[Dao-Chang], Xu, C.[Chang], Fu, D.M.[Dong-Mei],
Learning Degradation-Robust Spatiotemporal Frequency-Transformer for Video Super-Resolution,
PAMI(45), No. 12, December 2023, pp. 14888-14904.
IEEE DOI 2311
BibRef
Earlier: A1, A2, A3, A6, Only:
Learning Spatiotemporal Frequency-Transformer for Compressed Video Super-Resolution,
ECCV22(XVIII:257-273).
Springer DOI 2211
BibRef

Tuo, Z.X.[Zi-Xi], Yang, H.[Huan], Fu, J.L.[Jian-Long], Dun, Y.J.[Yu-Jie], Qian, X.M.[Xue-Ming],
Learning Data-Driven Vector-Quantized Degradation Model for Animation Video Super-Resolution,
ICCV23(13133-13143)
IEEE DOI Code:
WWW Link. 2401
BibRef

Hosseinpour, M.[Mina], Behnam, H.[Hamid], Shojaeifard, M.[Maryam],
Compressive sensing theory and neighborhood spatial-temporal information for frame rate improvement of dynamic ultrasonic imaging,
IJIST(31), No. 3, 2021, pp. 1334-1356.
DOI Link 2108
compressive sensing theory, dynamic ultrasonic imaging, frame rate improvement, neighborhood spatial-temporal information BibRef

Shi, Z.H.[Zhi-Hao], Liu, X.H.[Xiao-Hong], Shi, K.D.[Kang-Di], Dai, L.H.[Lin-Hui], Chen, J.[Jun],
Video Frame Interpolation via Generalized Deformable Convolution,
MultMed(24), 2022, pp. 426-439.
IEEE DOI 2202
Convolution, Interpolation, Kernel, Shape, Streaming media, Estimation, Task analysis, Generalized deformable convolution, video frame interpolation BibRef

Tran, Q.N.[Quang Nhat], Yang, S.H.[Shih-Hsuan],
Video frame interpolation via down-up scale generative adversarial networks,
CVIU(220), 2022, pp. 103434.
Elsevier DOI 2206
Video frame interpolation, Video frame generation, Deep learning, Generative adversarial networks, Generation network BibRef

Cheng, X.H.[Xian-Hang], Chen, Z.Z.[Zhen-Zhong],
Multiple Video Frame Interpolation via Enhanced Deformable Separable Convolution,
PAMI(44), No. 10, October 2022, pp. 7029-7045.
IEEE DOI 2209
Interpolation, Kernel, Convolution, Optical imaging, Optical distortion, Estimation, Nonlinear optics, separable convolution BibRef

Yun, I.[Ilwi], Lee, H.J.[Hyuk-Jae], Rhee, C.E.[Chae Eun],
AAGAN: Accuracy-Aware Generative Adversarial Network for Supervised Tasks,
CirSysVideo(32), No. 10, October 2022, pp. 6573-6583.
IEEE DOI 2210
Generative adversarial networks, Generators, Task analysis, Multitasking, Symbols, Linear programming, Image quality, frame interpolation BibRef

Li, Y.[Yu], Zhu, Y.[Ye], Li, R.T.[Ruo-Teng], Wang, X.T.[Xin-Tao], Luo, Y.[Yue], Shan, Y.[Ying],
Hybrid Warping Fusion for Video Frame Interpolation,
IJCV(130), No. 12, December 2022, pp. 2980-2993.
Springer DOI 2211
BibRef

Luo, Y.[Yao], Pan, J.S.[Jin-Shan], Tang, J.H.[Jin-Hui],
Bi-Directional Pseudo-Three-Dimensional Network for Video Frame Interpolation,
IP(31), 2022, pp. 6773-6788.
IEEE DOI 2211
Estimation, Interpolation, Kernel, Convolution, Feature extraction, Motion estimation, Correlation, Video frame interpolation, joint self-supervised and supervised training BibRef

Choi, M.[Myungsub], Choi, J.[Janghoon], Baik, S.[Sungyong], Kim, T.H.[Tae Hyun], Lee, K.M.[Kyoung Mu],
Test-Time Adaptation for Video Frame Interpolation via Meta-Learning,
PAMI(44), No. 12, December 2022, pp. 9615-9628.
IEEE DOI 2212
BibRef
Earlier:
Scene-Adaptive Video Frame Interpolation via Meta-Learning,
CVPR20(9441-9450)
IEEE DOI 2008
Interpolation, Adaptation models, Estimation, Task analysis, Visualization, Superresolution, Performance gain, MAML. Training, Computational modeling BibRef

Kong, L.T.[Ling-Tong], Liu, J.F.[Jin-Feng], Yang, J.[Jie],
Progressive Motion Context Refine Network for Efficient Video Frame Interpolation,
SPLetters(29), 2022, pp. 2338-2342.
IEEE DOI 2212
Interpolation, Optical imaging, Convolution, Decoding, Feature extraction, Optical losses, Optical signal processing, video frame interpolation BibRef

Kong, L.T.[Ling-Tong], Jiang, B.Y.[Bo-Yuan], Luo, D.H.[Dong-Hao], Chu, W.Q.[Wen-Qing], Huang, X.M.[Xiao-Ming], Tai, Y.[Ying], Wang, C.J.[Cheng-Jie], Yang, J.[Jie],
IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation,
CVPR22(1959-1968)
IEEE DOI 2210
Optical losses, Geometry, Interpolation, Layout, Streaming media, Feature extraction, Real-time systems, Low-level vision, Image and video synthesis and generation BibRef

Yu, Z.Y.[Zhi-Yang], Chen, X.J.[Xi-Jun], Ren, S.Q.[Shun-Qing],
Video Frame Interpolation With Learnable Uncertainty and Decomposition,
SPLetters(29), 2022, pp. 2642-2646.
IEEE DOI 2301
Uncertainty, Interpolation, Couplings, Neural networks, Convolution, Optical flow, Estimation, Signal decomposition, video frame interpolation BibRef

Yang, X.H.[Xiao-Hui], Zhang, H.R.[Hao-Ran], Qu, Z.[Zhe], Feng, Z.Q.[Zhi-Quan], Tian, J.L.[Jing-Lan],
Video frame interpolation via residual blocks and feature pyramid networks,
IET-IPR(17), No. 4, 2023, pp. 1060-1070.
DOI Link 2303
image processing, video signal processing BibRef

Yang, R.[Ren], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
Advancing Learned Video Compression With In-Loop Frame Prediction,
CirSysVideo(33), No. 5, May 2023, pp. 2410-2423.
IEEE DOI 2305
Video compression, Image coding, Streaming media, Ions, Standards, Interpolation, Prediction algorithms, Deep learning, in-loop prediction BibRef

Gao, Y.[Yue], Li, S.Q.[Si-Qi], Li, Y.P.[Yi-Peng], Guo, Y.D.[Yan-Dong], Dai, Q.H.[Qiong-Hai],
SuperFast: 200× Video Frame Interpolation via Event Camera,
PAMI(45), No. 6, June 2023, pp. 7764-7780.
IEEE DOI 2305
Cameras, Streaming media, Brightness, Interpolation, Task analysis, Lenses, Visualization, Video frame interpolation, event-enhanced, high-speed VFI dataset BibRef

Zhang, F.[Fuhua], Yang, C.[Chuang],
DSF-Net: Dual-Stream Fused Network for Video Frame Interpolation,
SPLetters(30), 2023, pp. 1122-1126.
IEEE DOI 2310
BibRef

Kong, L.T.[Ling-Tong], Jiang, B.[Boyuan], Luo, D.H.[Dong-Hao], Chu, W.Q.[Wen-Qing], Tai, Y.[Ying], Wang, C.J.[Cheng-Jie], Yang, J.[Jie],
Dynamic Frame Interpolation in Wavelet Domain,
IP(32), 2023, pp. 5296-5309.
IEEE DOI 2310
BibRef

Liu, M.[Meiqin], Xu, C.[Chenming], Yao, C.[Chao], Lin, C.Y.[Chun-Yu], Zhao, Y.[Yao],
JNMR: Joint Non-Linear Motion Regression for Video Frame Interpolation,
IP(32), 2023, pp. 5283-5295.
IEEE DOI Code:
WWW Link. 2310
BibRef

Li, Y.[Yanhao], Gardella, M.[Marina], Bammey, Q.[Quentin], Nikoukhah, T.[Tina], Grompone-von Gioi, R.[Rafael], Colom, M.[Miguel], Morel, J.M.[Jean-Michel],
A Signal-dependent Video Noise Estimator Via Inter-frame Signal Suppression,
IPOL(13), 2023, pp. 280-313.
DOI Link 2311
Code, Video Noise. BibRef
Earlier:
Video Signal-Dependent Noise Estimation via Inter-Frame Prediction,
ICIP22(1406-1410)
IEEE DOI 2211
Gaussian noise, Redundancy, Estimation, Energy measurement, Transforms, High frequency, Noise estimation, image processing, noise level function BibRef

Xiao, J.[Jing], Xu, K.[Kangmin], Hu, M.[Mengshun], Liao, L.[Liang], Wang, Z.[Zheng], Lin, C.W.[Chia-Wen], Wang, M.[Mi], Satoh, S.[Shin'ichi],
Progressive Motion Boosting for Video Frame Interpolation,
MultMed(25), 2023, pp. 8076-8090.
IEEE DOI 2312
BibRef

Hu, P.[Ping], Niklaus, S.[Simon], Zhang, L.[Lu], Sclaroff, S.[Stan], Saenko, K.[Kate],
Video Frame Interpolation With Many-to-Many Splatting and Spatial Selective Refinement,
PAMI(46), No. 2, February 2024, pp. 823-836.
IEEE DOI 2401
BibRef
Earlier: A1, A2, A4, A5, Only:
Many-to-many Splatting for Efficient Video Frame Interpolation,
CVPR22(3543-3552)
IEEE DOI 2210
Interpolation, Machine-to-machine communications, Visualization, Fuses, Motion estimation, Benchmark testing, Image and video synthesis and generation BibRef

Zhou, S.[Shili], Tan, W.M.[Wei-Min], Yan, B.[Bo],
A Motion Distillation Framework for Video Frame Interpolation,
MultMed(26), 2024, pp. 3728-3740.
IEEE DOI 2402
Training, Computational modeling, Optical flow, Kernel, Interpolation, Motion estimation, Correlation, Deep learning, optical flow BibRef

Lei, P.C.[Peng-Cheng], Fang, F.[Faming], Zeng, T.Y.[Tie-Yong], Zhang, G.X.[Gui-Xu],
Flow Guidance Deformable Compensation Network for Video Frame Interpolation,
MultMed(26), 2024, pp. 1801-1812.
IEEE DOI 2402
Task analysis, Estimation, Deformation, Interpolation, Convolution, Kernel, Optical imaging, Video frame interpolation, distillation learning BibRef

Zhu, G.S.[Guo-Song], Qin, Z.[Zhen], Ding, Y.[Yi], Liu, Y.[Yao], Qin, Z.G.[Zhi-Guang],
MFNet: Real-Time Motion Focus Network for Video Frame Interpolation,
MultMed(26), 2024, pp. 3251-3262.
IEEE DOI 2402
Interpolation, Optical imaging, Task analysis, Optical distortion, Memory management, Streaming media, Dynamics, video frame interpolation BibRef


Siyao, L.[Li], Gu, T.[Tianpei], Xiao, W.[Weiye], Ding, H.H.[Heng-Hui], Liu, Z.W.[Zi-Wei], Loy, C.C.[Chen Change],
Deep Geometrized Cartoon Line Inbetweening,
ICCV23(7257-7266)
IEEE DOI Code:
WWW Link. 2401
BibRef

Ji, X.[Xiang], Wang, Z.X.[Zhi-Xiang], Zhong, Z.H.[Zhi-Hang], Zheng, Y.Q.[Yin-Qiang],
Rethinking Video Frame Interpolation from Shutter Mode Induced Degradation,
ICCV23(12225-12234)
IEEE DOI 2401
BibRef

Zhao, L.[Lili], Sun, Z.Q.[Zhuo-Qun], Ren, L.[Lancao], Yin, Q.[Qian], Yang, L.[Lei], Guo, M.[Meng],
Learning Spatial-Temporal Embeddings for Sequential Point Cloud Frame Interpolation,
ICIP23(810-814)
IEEE DOI 2312
BibRef

Khalifeh, I.[Issa], Murn, L.[Luka], Mrak, M.[Marta], Izquierdo, E.[Ebroul],
Efficient Convolution and Transformer-based Network for Video Frame Interpolation,
ICIP23(1050-1054)
IEEE DOI 2312
BibRef

Morris, C.[Crispian], Danier, D.[Duolikun], Zhang, F.[Fan], Anantrasirichai, N.[Nantheera], Bull, D.R.[David R.],
ST-MFNET Mini: Knowledge Distillation-Driven Frame Interpolation,
ICIP23(1045-1049)
IEEE DOI Code:
WWW Link. 2312
BibRef

Lee, S.J.[Sang-Jin], Lee, H.[Hyeongmin], Shin, C.[Chajin], Son, H.[Hanbin], Lee, S.Y.[Sang-Youn],
Exploring Discontinuity for Video Frame Interpolation,
CVPR23(9791-9800)
IEEE DOI 2309
BibRef

Li, Z.[Zhen], Zhu, Z.L.[Zuo-Liang], Han, L.H.[Ling-Hao], Hou, Q.[Qibin], Guo, C.L.[Chun-Le], Cheng, M.M.[Ming-Ming],
AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolation,
CVPR23(9801-9810)
IEEE DOI 2309
BibRef

Plack, M.[Markus], Hullin, M.B.[Matthias B.], Briedis, K.M.[Karlis Martins], Gross, M.[Markus], Djelouah, A.[Abdelaziz], Schroers, C.[Christopher],
Frame Interpolation Transformer and Uncertainty Guidance,
CVPR23(9811-9821)
IEEE DOI 2309
BibRef

Mo, C.A.[Clinton A.], Hu, K.[Kun], Long, C.J.[Cheng-Jiang], Wang, Z.Y.[Zhi-Yong],
Continuous Intermediate Token Learning with Implicit Motion Manifold for Keyframe Based Motion Interpolation,
CVPR23(13894-13903)
IEEE DOI 2309
BibRef

Shang, W.[Wei], Ren, D.W.[Dong-Wei], Yang, Y.[Yi], Zhang, H.Z.[Hong-Zhi], Ma, K.[Kede], Zuo, W.M.[Wang-Meng],
Joint Video Multi-Frame Interpolation and Deblurring under Unknown Exposure Time,
CVPR23(13935-13944)
IEEE DOI 2309
BibRef

Kim, T.[Taewoo], Chae, Y.[Yujeong], Jang, H.K.[Hyun-Kurl], Yoon, K.J.[Kuk-Jin],
Event-based Video Frame Interpolation with Cross-Modal Asymmetric Bidirectional Motion Fields,
CVPR23(18032-18042)
IEEE DOI 2309
BibRef

Sun, L.[Lei], Sakaridis, C.[Christos], Liang, J.Y.[Jing-Yun], Sun, P.[Peng], Zhang, K.[Kai], Cao, J.[Jiezhang], Jiang, Q.[Qi], Wang, K.W.[Kai-Wei], Van Gool, L.J.[Luc J.],
Event-Based Frame Interpolation with Ad-hoc Deblurring,
CVPR23(18043-18052)
IEEE DOI 2309
BibRef

Yu, Z.Y.[Zhi-Yang], Zhang, Y.[Yu], Zou, D.Q.[Dong-Qing], Chen, X.[Xijun], Ren, J.S.[Jimmy S.], Ren, S.Q.[Shun-Qing],
Range-nullspace Video Frame Interpolation with Focalized Motion Estimation,
CVPR23(22159-22168)
IEEE DOI 2309
BibRef

Zhou, K.[Kun], Li, W.B.[Wen-Bo], Han, X.G.[Xiao-Guang], Lu, J.B.[Jiang-Bo],
Exploring Motion Ambiguity and Alignment for High-Quality Video Frame Interpolation,
CVPR23(22169-22179)
IEEE DOI 2309
BibRef

Zhang, G.Z.[Guo-Zhen], Zhu, Y.H.[Yu-Han], Wang, H.[Haonan], Chen, Y.X.[You-Xin], Wu, G.S.[Gang-Shan], Wang, L.M.[Li-Min],
Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation,
CVPR23(5682-5692)
IEEE DOI 2309
BibRef

Weng, W.M.[Wen-Ming], Zhang, Y.[Yueyi], Xiong, Z.W.[Zhi-Wei],
Event-based Blurry Frame Interpolation under Blind Exposure,
CVPR23(1588-1598)
IEEE DOI 2309
BibRef

Jin, X.[Xin], Wu, L.[Longhai], Chen, J.[Jie], Chen, Y.X.[You-Xin], Koo, J.[Jayoon], Hahm, C.H.[Cheul-Hee],
A Unified Pyramid Recurrent Network for Video Frame Interpolation,
CVPR23(1578-1587)
IEEE DOI 2309
BibRef

Paliwal, A.[Avinash], Tsarov, A.[Andrii], Kalantari, N.K.[Nima Khademi],
Implicit View-Time Interpolation of Stereo Videos Using Multi-Plane Disparities and Non-Uniform Coordinates,
CVPR23(888-898)
IEEE DOI 2309
BibRef

Kim, H.H.[Hannah Halin], Yu, S.[Shuzhi], Yuan, S.[Shuai], Tomasi, C.[Carlo],
Cross-attention Transformer for Video Interpolation,
ACCVWS22(325-342).
Springer DOI 2307
BibRef

Lin, X.[Xuhu], Zhao, L.[Lili], Liu, X.[Xi], Chen, J.W.[Jian-Wen],
Mvfi-net: Motion-aware Video Frame Interpolation Network,
ACCV22(III:340-356).
Springer DOI 2307
BibRef

Sridhar, P.[Pavithra], Aananth, V., Aggarwal, M.[Madhav], Velusamy, R.L.[R. Leela],
Transformer Based Motion In-betweening,
ACCVWS22(295-307).
Springer DOI 2307
BibRef

Yang, T.[Tao], Ren, P.R.[Pei-Ran], Xie, X.[Xuansong], Hua, X.S.[Xian-Sheng], Zhang, L.[Lei],
Beyond a Video Frame Interpolator: A Space Decoupled Learning Approach to Continuous Image Transition,
VIPriors22(738-755).
Springer DOI 2304
BibRef

Jin, X.[Xin], Wu, L.[Longhai], Shen, G.[Guotao], Chen, Y.X.[You-Xin], Chen, J.[Jie], Koo, J.[Jayoon], Hahm, C.H.[Cheul-Hee],
Enhanced Bi-directional Motion Estimation for Video Frame Interpolation,
WACV23(5038-5046)
IEEE DOI 2302
Interpolation, Adaptation models, Fuses, Motion estimation, Ultraviolet sources, Bidirectional control, Benchmark testing, Low-level and physics-based vision BibRef

Deng, H.Q.[Han-Qiu], Zhang, Z.X.[Zhao-Xiang], Zou, S.H.[Shi-Hao], Li, X.Y.[Xing-Yu],
Bi-directional Frame Interpolation for Unsupervised Video Anomaly Detection,
WACV23(2633-2642)
IEEE DOI 2302
Interpolation, Visualization, Dynamics, Video sequences, Estimation, Bidirectional control, Benchmark testing BibRef

Kalluri, T.[Tarun], Pathak, D.[Deepak], Chandraker, M.[Manmohan], Tran, D.[Du],
FLAVR: Flow-Agnostic Video Representations for Fast Frame Interpolation,
WACV23(2070-2081)
IEEE DOI 2302
Training, Interpolation, Solid modeling, Computational modeling, Estimation, image and video synthesis BibRef

Niklaus, S.[Simon], Hu, P.[Ping], Chen, J.[Jiawen],
Splatting-based Synthesis for Video Frame Interpolation,
WACV23(713-723)
IEEE DOI 2302
Deep learning, Interpolation, Image resolution, Neural networks, Image sequences, Computational efficiency, image and video synthesis BibRef

Figueirêdo, P.[Pedro], Paliwal, A.[Avinash], Kalantari, N.K.[Nima Khademi],
Frame Interpolation for Dynamic Scenes with Implicit Flow Encoding,
WACV23(218-228)
IEEE DOI 2302
Interpolation, Image coding, Heuristic algorithms, Brightness, Lighting, Optical flow, Algorithms: Computational photography BibRef

Reda, F.[Fitsum], Kontkanen, J.[Janne], Tabellion, E.[Eric], Sun, D.Q.[De-Qing], Pantofaru, C.[Caroline], Curless, B.[Brian],
FILM: Frame Interpolation for Large Motion,
ECCV22(VII:250-266).
Springer DOI 2211
BibRef

Oh, J.H.[Ji-Hyong], Kim, M.C.[Mun-Churl],
DeMFI: Deep Joint Deblurring and Multi-frame Interpolation with Flow-Guided Attentive Correlation and Recursive Boosting,
ECCV22(VII:198-215).
Springer DOI 2211
BibRef

Wu, S.[Song], You, K.[Kaichao], He, W.H.[Wei-Hua], Yang, C.[Chen], Tian, Y.[Yang], Wang, Y.[Yaoyuan], Zhang, Z.Y.[Zi-Yang], Liao, J.X.[Jian-Xing],
Video Interpolation by Event-Driven Anisotropic Adjustment of Optical Flow,
ECCV22(VII:267-283).
Springer DOI 2211
BibRef

Liu, J.F.[Jin-Feng], Kong, L.T.[Ling-Tong], Yang, J.[Jie],
ATCA: An ARC Trajectory Based Model with Curvature Attention for Video Frame Interpolation,
ICIP22(1486-1490)
IEEE DOI 2211
Deep learning, Interpolation, Memory management, Benchmark testing, Trajectory, Video frame interpolation, Optical flow, Curvature attention BibRef

Danier, D.[Duolikun], Zhang, F.[Fan], Bull, D.[David],
Enhancing Deformable Convolution Based Video Frame Interpolation with Coarse-To-Fine 3D CNN,
ICIP22(1396-1400)
IEEE DOI 2211
Interpolation, Solid modeling, Convolution, Databases, Benchmark testing, Feature extraction, Video Frame Interpolation, 3D CNN BibRef

Huang, Z.W.[Zhe-Wei], Zhang, T.Y.[Tian-Yuan], Heng, W.[Wen], Shi, B.X.[Bo-Xin], Zhou, S.C.[Shu-Chang],
Real-Time Intermediate Flow Estimation for Video Frame Interpolation,
ECCV22(XIV:624-642).
Springer DOI 2211
BibRef

Yu, Z.Y.[Zhi-Yang], Zhang, Y.[Yu], Xiang, X.[Xujie], Zou, D.Q.[Dong-Qing], Chen, X.[Xijun], Ren, J.S.[Jimmy S.],
Deep Bayesian Video Frame Interpolation,
ECCV22(XV:144-160).
Springer DOI 2211
BibRef

Kulhánek, J.[Jonáš], Derner, E.[Erik], Sattler, T.[Torsten], Babuška, R.[Robert],
ViewFormer: NeRF-Free Neural Rendering from Few Images Using Transformers,
ECCV22(XV:198-216).
Springer DOI 2211
BibRef

Hou, Q.Q.[Qi-Qi], Ghildyal, A.[Abhijay], Liu, F.[Feng],
A Perceptual Quality Metric for Video Frame Interpolation,
ECCV22(XV:234-253).
Springer DOI 2211
BibRef

Dai, M.Y.[Meng-Yu], Hang, H.B.[Hai-Bin], Guo, X.Y.[Xiao-Yang],
Adaptive Feature Interpolation for Low-Shot Image Generation,
ECCV22(XV:254-270).
Springer DOI 2211
BibRef

Zhuo, L.[Long], Wang, G.[Guangcong], Li, S.[Shikai], Wu, W.[Wayne], Liu, Z.W.[Zi-Wei],
Fast-Vid2Vid: Spatial-Temporal Compression for Video-to-Video Synthesis,
ECCV22(XV:289-305).
Springer DOI 2211
BibRef

Shangguan, W.T.[Wen-Tao], Sun, Y.[Yu], Gan, W.J.[Wei-Jie], Kamilov, U.S.[Ulugbek S.],
Learning Cross-Video Neural Representations for High-Quality Frame Interpolation,
ECCV22(XV:511-528).
Springer DOI 2211
BibRef

Chen, S.H.[Shu-Hong], Zwicker, M.[Matthias],
Improving the Perceptual Quality of 2D Animation Interpolation,
ECCV22(XVII:271-287).
Springer DOI 2211
BibRef

Shen, W.[Wang], Ming, C.[Cheng], Bao, W.B.[Wen-Bo], Zhai, G.T.[Guang-Tao], Chenn, L.[Li], Gao, Z.Y.[Zhi-Yong],
Enhanced Deep Animation Video Interpolation,
ICIP22(31-35)
IEEE DOI 2211
Training, Interpolation, Visualization, Adaptation models, Pipelines, Training data, animation frame interpolation, nonlinear motion, neural network BibRef

Shi, Z.H.[Zhi-Hao], XU, X.Y.[Xiang-Yu], Liu, X.H.[Xiao-Hong], Chen, J.[Jun], Yang, M.H.[Ming-Hsuan],
Video Frame Interpolation Transformer,
CVPR22(17461-17470)
IEEE DOI 2210
Interpolation, Convolution, Neural networks, Memory management, Transformers, Pattern recognition, Low-level vision, Image and video synthesis and generation BibRef

Danier, D.[Duolikun], Zhang, F.[Fan], Bull, D.[David],
ST-MFNet: A Spatio-Temporal Multi-Flow Network for Frame Interpolation,
CVPR22(3511-3521)
IEEE DOI 2210
Deep learning, Interpolation, Visualization, Solid modeling, Heuristic algorithms, Image and video synthesis and generation, Deep learning architectures and techniques BibRef

Dutta, S.[Saikat], Subramaniam, A.[Arulkumar], Mittal, A.[Anurag],
Non-linear Motion Estimation for Video Frame Interpolation using Space-time Convolutions,
CLIC22(1725-1730)
IEEE DOI 2210
Interpolation, Adaptation models, Solid modeling, Convolution, Video compression, Prediction algorithms BibRef

Lu, L.Y.[Li-Ying], Wu, R.Z.[Rui-Zheng], Lin, H.[Huaijia], Lu, J.B.[Jiang-Bo], Jia, J.Y.[Jia-Ya],
Video Frame Interpolation with Transformer,
CVPR22(3522-3532)
IEEE DOI 2210
Interpolation, Correlation, Convolution, Aggregates, Face recognition, Computational modeling, Video analysis and understanding BibRef

Argaw, D.M.[Dawit Mureja], Kweon, I.S.[In So],
Long-term Video Frame Interpolation via Feature Propagation,
CVPR22(3533-3542)
IEEE DOI 2210
Interpolation, Tracking, Motion estimation, Computer network reliability, Pattern recognition, Reliability, Motion and tracking BibRef

Yu, Z.Y.[Zhi-Yang], Zhang, Y.[Yu], Liu, D.[Deyuan], Zou, D.Q.[Dong-Qing], Chen, X.J.[Xi-Jun], Liu, Y.B.[Ye-Bin], Ren, J.[Jimmy],
Training Weakly Supervised Video Frame Interpolation with Events,
ICCV21(14569-14578)
IEEE DOI 2203
Training, Interpolation, Supervised learning, Dynamics, Training data, Transformers, Feature extraction, Vision applications and systems BibRef

Sim, H.[Hyeonjun], Oh, J.[Jihyong], Kim, M.C.[Mun-Churl],
XVFI: eXtreme Video Frame Interpolation,
ICCV21(14469-14478)
IEEE DOI 2203
Training, Interpolation, Ultraviolet sources, Benchmark testing, Cameras, Robustness, Image and video synthesis, Vision applications and systems BibRef

Choi, M.[Myungsub], Lee, S.Y.[Su-Young], Kim, H.[Heewon], Lee, K.M.[Kyoung Mu],
Motion-Aware Dynamic Architecture for Efficient Frame Interpolation,
ICCV21(13819-13828)
IEEE DOI 2203
Interpolation, Adaptation models, Costs, Computational modeling, Dynamics, Superresolution, Image and video synthesis, Emergency Reviewer BibRef

Lee, S.[Sungho], Choi, N.[Narae], Choi, W.I.[Woong Il],
Enhanced Correlation Matching based Video Frame Interpolation,
WACV22(3123-3131)
IEEE DOI 2202
Training, Interpolation, Image motion analysis, Correlation, Convolution, Estimation, Computational Photography, Image and Video Synthesis Image Processing -> Image Restoration BibRef

Alexandre, D.[David], Hang, H.M.[Hsueh-Ming], Peng, W.H.[Wen-Hsiao], Domanski, M.[Marek],
Deep Video Compression for Interframe Coding,
ICIP21(2124-2128)
IEEE DOI 2201
Extrapolation, Image coding, Video compression, Decoding, Video codecs, Optical flow, Deep learning, video compression, video extrapolation BibRef

Wang, Z.F.[Zhen-Fang], Wang, Y.J.[Yan-Jiang], Shao, S.[Shuai], Liu, B.D.[Bao-Di],
OPS-Net: Over-Parameterized Sharing Networks for Video Frame Interpolation,
ICIP21(1974-1978)
IEEE DOI 2201
Training, Deep learning, Interpolation, Image processing, Video sequences, Spatiotemporal phenomena, Over-parameterization BibRef

Xue, F.Y.[Fan-Yong], Li, J.[Jie], Wu, C.T.[Chen-Tao],
A Novel All-In-One Grid Network for Video Frame Interpolation,
ICIP21(1969-1973)
IEEE DOI 2201
Performance evaluation, Interpolation, Image synthesis, Computational modeling, Estimation, Feature extraction, optical flow estimation BibRef

Bhatia, H.[Harsh], Petruzza, S.N.[Steve N.], Anirudh, R.[Rushil], Gyulassy, A.G.[Attila G.], Kirby, R.M.[Robert M.], Pascucci, V.[Valerio], Bremer, P.T.[Peer-Timo],
Data-Driven Estimation of Temporal-Sampling Errors in Unsteady Flows,
ISVC21(I:235-248).
Springer DOI 2112
BibRef

Wijma, R.[Ruth], You, S.[Shaodi], Li, Y.[Yu],
Multi-Level Adaptive Separable Convolution for Large-Motion Video Frame Interpolation,
PBDL21(1127-1135)
IEEE DOI 2112
Interpolation, Adaptation models, Analytical models, Convolution, Benchmark testing BibRef

Ding, T.Y.[Tian-Yu], Liang, L.[Luming], Zhu, Z.H.[Zhi-Hui], Zharkov, I.[Ilya],
CDFI: Compression-Driven Network Design for Frame Interpolation,
CVPR21(7997-8007)
IEEE DOI 2111
Performance evaluation, Interpolation, Visualization, Redundancy, Computer architecture, Performance gain BibRef

Paikin, G.[Genady], Ater, Y.[Yotam], Shaul, R.[Roy], Soloveichik, E.[Evgeny],
EFI-Net: Video Frame Interpolation from Fusion of Events and Frames,
EventVision21(1291-1301)
IEEE DOI 2109
Interpolation, Image color analysis, Lighting, Streaming media, Cameras, Sensors, Pattern recognition BibRef

Tulyakov, S.[Stepan], Bochicchio, A.[Alfredo], Gehrig, D.[Daniel], Georgoulis, S.[Stamatios], Li, Y.Y.[Yuan-You], Scaramuzza, D.[Davide],
Time Lens++: Event-based Frame Interpolation with Parametric Nonlinear Flow and Multi-scale Fusion,
CVPR22(17734-17743)
IEEE DOI 2210
Interpolation, Motion estimation, Memory management, Dynamics, Cameras, Pattern recognition, Computational photography, Image and video synthesis and generation BibRef

Tulyakov, S.[Stepan], Gehrig, D.[Daniel], Georgoulis, S.[Stamatios], Erbach, J.[Julius], Gehrig, M.[Mathias], Li, Y.[Yuanyou], Scaramuzza, D.[Davide],
Time Lens: Event-based Video Frame Interpolation,
CVPR21(16150-16159)
IEEE DOI
HTML Version. 2106
Code, Frame Interpolation. Dataset, Frame Interpolation. Interpolation, Visualization, Image color analysis, Benchmark testing, Cameras, Sensors, Pattern recognition BibRef

Schuster, R.[René], Wasenmüller, O.[Oliver], Unger, C.[Christian], Stricker, D.[Didier],
SSGP: Sparse Spatial Guided Propagation for Robust and Generic Interpolation,
WACV21(197-206)
IEEE DOI 2106
Interpolation, Image motion analysis, Convolution, Image edge detection, Market research, Robustness BibRef

Liu, K.N.[Kang-Ning], Gu, S.H.[Shu-Hang], Romero, A.[Andrés], Timofte, R.[Radu],
Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning,
WACV21(1029-1039)
IEEE DOI 2106
Interpolation, Recurrent neural networks, Computational modeling, Semantics, Training data BibRef

Suzuki, K.[Keito], Ikehara, M.[Masaaki],
Residual Learning of Video Frame Interpolation Using Convolutional LSTM,
ICPR21(1499-1504)
IEEE DOI 2105
Interpolation, Uncertainty, Motion estimation, Video sequences, Neural networks, Cameras, Spatiotemporal phenomena BibRef

Guo, Y., Liu, Z., Chen, Z., Liu, S.,
Deep Inter Coding with Interpolated Reference Frame for Hierarchical Coding Structure,
VCIP20(302-305)
IEEE DOI 2102
Encoding, Interpolation, Training, Streaming media, Convolution, Motion estimation, Neural networks, Inter Prediction, Convolutional Neural Network (CNN) BibRef

Zhang, H.X.[Hao-Xian], Zhao, Y.[Yang], Wang, R.G.[Rong-Gang],
A Flexible Recurrent Residual Pyramid Network for Video Frame Interpolation,
ECCV20(XXV:474-491).
Springer DOI 2011
BibRef

Chi, Z.X.[Zhi-Xiang], Nasiri, R.M.[Rasoul Mohammadi], Liu, Z.[Zheng], Lu, J.W.[Ju-Wei], Tang, J.[Jin], Plataniotis, K.N.[Konstantinos N.],
All at Once: Temporally Adaptive Multi-frame Interpolation with Advanced Motion Modeling,
ECCV20(XXVII:107-123).
Springer DOI 2011
BibRef

Lee, S., Lee, H., Kim, T., Lee, S.,
Extrapolative-Interpolative Cycle-Consistency Learning For Video Frame Extrapolation,
ICIP20(1571-1575)
IEEE DOI 2011
Extrapolation, Interpolation, Training, Mathematical model, Task analysis, Computational modeling, Cycle-consistency loss BibRef

Zhuang, J.K.[Jian-Kai], Qin, Z.C.[Zeng-Chang], Chen, J.L.[Jia-Lu], Wan, T.[Tao],
A Lightweight Network Model For Video Frame Interpolation Using Spatial Pyramids,
ICIP20(543-547)
IEEE DOI 2011
Interpolation, Computational modeling, Estimation, Optical transmitters, Training, Machine learning, Deep learning BibRef

Kokaram, A., Singh, D., Robinson, S.,
A Bayesian View of Frame Interpolation and a Comparison with Existing Motion Picture Effects Tools,
ICIP20(553-557)
IEEE DOI 2011
Interpolation, Motion pictures, Optical imaging, Estimation, Image reconstruction, Bayes methods, Motion estimation, motion estimation BibRef

Murn, L., Blasi, S., Smeaton, A.F., O'Connor, N.E., Mrak, M.,
Interpreting CNN For Low Complexity Learned Sub-Pixel Motion Compensation In Video Coding,
ICIP20(798-802)
IEEE DOI 2011
Artificial neural networks, Complexity theory, Interpolation, Encoding, Video coding, Training, Kernel, inter prediction BibRef

Park, J.[Junheum], Kim, J.[Jintae], Kim, C.S.[Chang-Su],
BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation,
CVPR23(1568-1577)
IEEE DOI 2309
BibRef

Park, J.[Junheum], Lee, C.[Chul], Kim, C.S.[Chang-Su],
Asymmetric Bilateral Motion Estimation for Video Frame Interpolation,
ICCV21(14519-14528)
IEEE DOI 2203
Interpolation, Codes, Heuristic algorithms, Motion estimation, Dynamics, Filtering algorithms, Image and video synthesis, Motion and tracking BibRef

Park, J.[Junheum], Ko, K.[Keunsoo], Lee, C.[Chul], Kim, C.S.[Chang-Su],
BMBC: Bilateral Motion Estimation with Bilateral Cost Volume for Video Interpolation,
ECCV20(XIV:109-125).
Springer DOI 2011
BibRef

Gui, S., Wang, C., Chen, Q., Tao, D.,
FeatureFlow: Robust Video Interpolation via Structure-to-Texture Generation,
CVPR20(14001-14010)
IEEE DOI 2008
Feature extraction, Interpolation, Optical imaging, Generators, Image edge detection, Task analysis, Convolution BibRef

Shen, W., Bao, W., Zhai, G., Chen, L., Min, X., Gao, Z.,
Blurry Video Frame Interpolation,
CVPR20(5113-5122)
IEEE DOI 2008
Interpolation, Image restoration, Cameras, Degradation, Optical network units, Kernel, Computational modeling BibRef

Niklaus, S., Liu, F.,
Softmax Splatting for Video Frame Interpolation,
CVPR20(5436-5445)
IEEE DOI 2008
Interpolation, Optical imaging, Task analysis, Feature extraction, Estimation, Image generation, Optical buffering BibRef

Lee, H., Kim, T., Chung, T., Pak, D., Ban, Y., Lee, S.,
AdaCoF: Adaptive Collaboration of Flows for Video Frame Interpolation,
CVPR20(5315-5324)
IEEE DOI 2008
Kernel, Interpolation, Feature extraction, Task analysis, Collaboration, Convolution, Neural networks BibRef

Reda, F., Sun, D., Dundar, A.[Aysegul], Shoeybi, M., Liu, G., Shih, K.J.[Kevin J.], Tao, A.[Anrew], Kautz, J., Catanzaro, B.[Bryan],
Unsupervised Video Interpolation Using Cycle Consistency,
ICCV19(892-900)
IEEE DOI 2004
interpolation, neural nets, optimisation, unsupervised learning, video signal processing, cycle consistency, Training data BibRef

Yu, S., Park, B., Jeong, J.,
PoSNet: 4x Video Frame Interpolation Using Position-Specific Flow,
AIM19(3503-3511)
IEEE DOI 2004
Code, Video Interpolation.
WWW Link. image resolution, image sequences, interpolation, video signal processing, video frame interpolation, Video Enhancement BibRef

Choi, J., Kweon, I.S.,
DIFRINT: Deep Iterative Frame Interpolation for Full-Frame Video Stabilization,
MMVAMTC19(3732-3736)
IEEE DOI 2004
interpolation, iterative methods, jitter, motion estimation, video signal processing, frame boundaries, video frames, Self supervised learning BibRef

Li, S., Xu, X., Pan, Z., Sun, W.,
Quadratic Video Interpolation for VTSR Challenge,
AIM19(3427-3431)
IEEE DOI 2004
interpolation, video signal processing, VTSR challenge, quadratic video interpolation algorithm, image manipulation, CNN BibRef

Wang, Y.[Yang], Huang, H.B.[Hai-Bin], Wang, C.[Chuan], He, T.[Tong], Wang, J.[Jue], Hoai, M.[Minh],
GIF2Video: Color Dequantization and Temporal Interpolation of GIF Images,
CVPR19(1419-1428).
IEEE DOI 2002
BibRef

Yuan, L.Z.[Liang-Zhe], Chen, Y.[Yibo], Liu, H.T.[Han-Tian], Kong, T.[Tao], Shi, J.B.[Jian-Bo],
Zoom-In-To-Check: Boosting Video Interpolation via Instance-Level Discrimination,
CVPR19(12175-12183).
IEEE DOI 2002
BibRef

Bao, W.B.[Wen-Bo], Lai, W.S.[Wei-Sheng], Ma, C.[Chao], Zhang, X.Y.[Xiao-Yun], Gao, Z.Y.[Zhi-Yong], Yang, M.H.[Ming-Hsuan],
Depth-Aware Video Frame Interpolation,
CVPR19(3698-3707).
IEEE DOI 2002
BibRef

Peleg, T.[Tomer], Szekely, P.[Pablo], Sabo, D.[Doron], Sendik, O.[Omry],
IM-Net for High Resolution Video Frame Interpolation,
CVPR19(2393-2402).
IEEE DOI 2002
BibRef

Xia, S., Yang, W., Hu, Y., Liu, J.,
Deep Inter Prediction Via Pixel-Wise Motion Oriented Reference Generation,
ICIP19(1710-1774)
IEEE DOI 1910
Inter prediction, frame interpolation, deep learning, video coding BibRef

Zhang, H., Li, L., Song, L., Yang, X., Li, Z.,
Advanced CNN Based Motion Compensation Fractional Interpolation,
ICIP19(709-713)
IEEE DOI 1910
Video Coding, Convolutional Neural Network, Fractional Interpolation BibRef

Zhou, L., Chen, Y., Tian, X., Jiang, R.,
Frame Interpolation Using Phase and Amplitude Feature Pyramids,
ICIP19(4190-4194)
IEEE DOI 1910
Gabor filtering, frame interpolation, phase-based method, neural network BibRef

Jayashankar, T., Moulin, P., Blu, T., Gilliam, C.,
Lap-Based Video Frame Interpolation,
ICIP19(4195-4199)
IEEE DOI 1910
Optical flow, Convolutional neural network, Lucas-Kanade algorithm, Video interpolation, Splines BibRef

Kidani, Y., Kawamura, K., Unno, K., Naito, S.,
Blocksize-QP Dependent Intra Interpolation Filters,
ICIP19(4125-4129)
IEEE DOI 1910
VVC, video coding, intra angular prediction, intra interpolation filter BibRef

Narita, R., Hirakawa, K., Aizawa, K.,
Optical Flow Based Line Drawing Frame Interpolation Using Distance Transform to Support Inbetweenings,
ICIP19(4200-4204)
IEEE DOI 1910
2D animation, inbetweening, optical flow BibRef

Arif, F.[Fahim], Amin, S.[Sundas], Ghafoor, A.[Abdul], Riaz, M.M.[M. Mohsin],
Frame Interpolation Using Phase Information and Guided Image Filtering,
CIAP19(II:249-259).
Springer DOI 1909
BibRef

Hannemose, M.[Morten], Jensen, J.N.[Janus Nørtoft], Einarsson, G.[Gudmundur], Wilm, J.[Jakob], Dahl, A.B.[Anders Bjorholm], Frisvad, J.R.[Jeppe Revall],
Video Frame Interpolation via Cyclic Fine-Tuning and Asymmetric Reverse Flow,
SCIA19(311-323).
Springer DOI 1906
BibRef

Jiang, H., Sun, D., Jampani, V., Yang, M., Learned-Miller, E.G., Kautz, J.,
Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation,
CVPR18(9000-9008)
IEEE DOI 1812
Optical imaging, Interpolation, Adaptive optics, Cognition, Computational modeling, Bidirectional control, Cameras BibRef

Meyer, S., Djelouah, A., McWilliams, B., Sorkine-Hornung, A., Gross, M.[Markus], Schroers, C.[Christopher],
PhaseNet for Video Frame Interpolation,
CVPR18(498-507)
IEEE DOI 1812
Interpolation, Optical imaging, Optical computing, Neural networks, Image reconstruction, Lighting BibRef

Niklaus, S., Liu, F.,
Context-Aware Synthesis for Video Frame Interpolation,
CVPR18(1701-1710)
IEEE DOI 1812
Interpolation, Adaptive optics, Neural networks, Optical computing, Optical imaging, Estimation BibRef

Wu, C.Y.[Chao-Yuan], Singhal, N.[Nayan], Krähenbühl, P.[Philipp],
Video Compression Through Image Interpolation,
ECCV18(VIII: 425-440).
Springer DOI 1810
BibRef

Chiang, C.H., Han, J., Vitvitskyy, S., Mukherjee, D., Xu, Y.,
Adaptive interpolation filter scheme in AV1,
ICIP17(934-937)
IEEE DOI 1803
Adders, Cutoff frequency, Encoding, Hardware, Interpolation, Kernel, Passband, Interpolation filter, adaptive filter, motion compensated prediction BibRef

Lin, W.T., Nanjundaswamy, T., Rose, K.,
Adaptive interpolated motion compensated prediction,
ICIP17(943-947)
IEEE DOI 1803
Bit rate, Decoding, Estimation, Indexes, Motion compensation, Predictive models, Training, Video coding, adaptation, motion compensation BibRef

Niklaus, S.[Simon], Mai, L.[Long], Wang, O.[Oliver],
Revisiting Adaptive Convolutions for Video Frame Interpolation,
WACV21(1098-1108)
IEEE DOI 2106
Interpolation, Image filtering, Task analysis, Optimization, Image denoising BibRef

Niklaus, S.[Simon], Mai, L.[Long], Liu, F.,
Video Frame Interpolation via Adaptive Separable Convolution,
ICCV17(261-270)
IEEE DOI 1802
BibRef
And:
Video Frame Interpolation via Adaptive Convolution,
CVPR17(2270-2279)
IEEE DOI 1711
convolution, image motion analysis, image sampling, image sequences, interpolation, neural nets. Image color analysis, Kernel, Optical computing, Optical imaging BibRef

Meyer, S.[Simone], Wang, O.[Oliver], Zimmer, H.[Henning], Grosse, M.[Max], Sorkine-Hornung, A.[Alexander],
Phase-based frame interpolation for video,
CVPR15(1410-1418)
IEEE DOI 1510
BibRef

Jiang, X.B.[Xiu-Bao], Wang, R.G.[Rong-Gang], Luo, J.J.[Jia-Jia], Wang, Z.Y.[Zhen-Yu], Gao, W.[Wen],
Robust view interpolation with mesh cutting,
VCIP16(1-4)
IEEE DOI 1701
Color BibRef

Tang, C.X.[Chuan-Xin], Wang, R.G.[Rong-Gang], Wang, W.M.[Wen-Min], Gao, W.[Wen],
A new frame interpolation method with pixel-level motion vector field,
VCIP14(350-353)
IEEE DOI 1504
image motion analysis BibRef

Rakêt, L.L.[Lars Lau], Roholm, L.[Lars], Bruhn, A.[Andrés], Weickert, J.[Joachim],
Motion Compensated Frame Interpolation with a Symmetric Optical Flow Constraint,
ISVC12(I: 447-457).
Springer DOI 1209
BibRef

Yu, Z.F.[Zhe-Fei], Wang, Z.Y.[Zhang-Yang], Hu, Z.[Zeng], Ling, Q.[Qing], Li, H.Q.[Hou-Qiang],
Video frame interpolation using 3-D total variation regularized completion,
ICIP12(857-860).
IEEE DOI 1302
BibRef

Yu, Z.F.[Zhe-Fei], Wang, Z.Y.[Zhang-Yang], Hu, Z.[Zeng], Li, H.Q.[Hou-Qiang], Ling, Q.[Qing],
Video error concealment via total variation regularized matrix completion,
ICIP12(1633-1636).
IEEE DOI 1302
BibRef

Huang, Y.J.[Yu-Jie], Lin, Y.Y.[Yin-Yi],
Motion compensated frame interpolation using skipped frame information,
VCIP11(1-4).
IEEE DOI 1201
BibRef

He, S.Q.[Su-Qin], Zhao, P.M.[Pu-Ming], Yan, J.Y.[Jin-Yu],
A New Global Bi-Directional Motion Compensation Frame Interpolation for Rate Control in H.264/AVC CODEC,
CISP09(1-6).
IEEE DOI 0910
BibRef

Lee, Y.L.[Yen-Lin], Nguyen, T.[Truong],
Fast one-pass motion compensated frame interpolation in high-definition video processing,
ICIP09(369-372).
IEEE DOI 0911
BibRef

Mishima, N.[Nao], Itoh, G.[Goh],
Novel frame interpolation method for hold-type displays,
ICIP04(III: 1473-1476).
IEEE DOI 0505
BibRef

Yoon, S.C., Ahuja, N.,
Frame Interpolation Using Transmitted Block-based Motion Vectors,
ICIP01(III: 856-859).
IEEE DOI 0108
BibRef

Martins, F.C.M.[Fernando C.M.],
Real-time video frame rate adaptation based on warping of edge-preserving meshes,
ICIP99(III:948-952).
IEEE DOI BibRef 9900

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Video Prediction .


Last update:Mar 16, 2024 at 20:36:19