Selected Publications:
2021
•G. Li, Z. Liu, R. Shi, Z. Hu, W. Wei, Y. Wu, M. Huang, and H. Ling.
“Personal Fixations-Based Object Segmentation with Object Localization
and Boundary Preservation," in IEEE Transactions on Image Processing,
vol. 30, pp. 1461-1475, Jan. 2021.
•W. Wei, Z. Liu, L. Huang, Z. Wang, W. Chen, T. Zhang, J. Wang, and L.
Xu. “Identify autism spectrum disorder via dynamic filter and deep
spatiotemporal feature extraction,” Signal Processing: Image
Communication, vol. 95, pp. 116195, May. 2021.
•Z. Wang, Z. Liu, W. Wei, and H. Duan. “SalED: Saliency prediction
with a pithy encoder-decoder architecture sensing local and global
information”, Image and Vision Computing, vol. 109, pp. 104149, May.
2021.
•G. Li, Z. Liu, M. Chen, Z. Bai, W. Wei, W. Lin, and H. Ling.
“Hierarchical Alternate Interaction Network for RGB-D Salient Object
Detection," in IEEE Transactions on Image Processing, vol. 30, pp.
3528-3542, Mar. 2021.
2020
•L.Huang, W. Wei, Z. Liu*, T. Zhang, J. Wang, L. Xu, W. Chen and O. Le
Meur,“Effective schizophrenia recognition using discriminative eye
movement features and model-metric based features”，Pattern recognition
letters, 2020, pp.608-616.
•W. Wei, Z. Liu, L. Huang, A. Nebout, O. Le Meur, T. Zhang, J. Wang,
and L. Xu,“Predicting atypical visual saliency for autism spectrum
disorder via scale-adaptive inception module and discriminative region
enhancement lose" Neurocomputing,doi.org/10.1016/j.neucom.2020.06.125.
•G. Li, Z. Liu, L. Ye,Y. Wang and H. Ling,“Cross-Modal Weighting
Network for RGB-D Salient Object Detection”，European Conference on
Computer Vision (ECCV), 2020.
•G. Li, Z. Liu, and H. Ling,“ICNet: Information Conversion Network
for RGB-D Based Salient Object Detection”，IEEE Transactions on Image
Processing, doi: 10.1109/TIP.2020.2976689, 2020.
•M. Chen, Z. Liu, L. Ye and Y. Wang,“Attentional coarse-and-fine
generative adversarial networks for image inpainting”，Neurocomputing
Volume 405, 10 September 2020, Pages 259-269.
•J. Ren, Z. Liu, G. Li, X. Zhou, C. Bai, and G. Sun,“Co-saliency
detection using collaborative feature extraction and high-to-low feature
integration”，International Conference on Multimedia and Expo (ICME),
London, United Kingdom, Jul. 2020.
•Q. Jiao, Z. Liu, G. Li, L, Ye and Y. Wang,“Fine-grained image
classification with coarse and fine labels on one-shot
learning",International Conference on Multimedia and Expo
Workshop(ICMEW), London, United Kingdom, Jul. 2020.
•Y. Wu, Z. Liu, and X. Zhou,“Saliency detection using adversarial
learning networks”,Journal of Visual Communication and Image
Representation, doi.org/10.1016/j.jvcir.2020.102761, 2020.
2019
•.L. Ye, M. Rochan, Z. Liu and Y. Wang,“Cross-Modal Self-Attention
Network for Referring Image Segmentation”,Proceedings of the IEEE
Conference on Computer Vision and Pattern Recognition(CVPR), 2019,
pp.10502-10511,
•J. Ren, Z. Liu, X. Zhou, C. Bai and G. Sun,“Co-saliency detection
via integration of multi-layer convolutional features and inter-image
propagation”,Neurocomputing, doi.org/10.1016/j.neucom.2019.09.010.
•G. Li, Z. Liu, R. Shi, and W. Wei,“Constrained Fixation Point based
Segmentation via Deep Neural Network”,Neurocomputing, vol. 368, pp.
180-187, Nov. 2019.
•W. Wei, Z. Liu, L. Huang, A. Nebout, and O. Le Meur,“Saliency
Prediction via Multi-Level Features and Deep Supervision for Children
with Autism Spectrum Disorder”,IEEE International Conference Multimedia
Expo Grand Challenge, 2019, pp.621–624.
•M. Huang, Z. Liu, L. Ye, X. Zhou and Y. Wang,"Saliency detection
via multi-level integration and multi-scale fusion neural
networks",Neurocomputing, vol. 364, pp. 310-321, Oct. 2019.
•Q. Jiao, Z. Liu, L. Ye and Y. Wang,"Weakly labeled fine-grained
classification with hierarchy relationship of fine and coarse
labels",Journal of Visual Communication and Image Representation, vol.
63, Aug. 2019.
•Y. Ding, Z. Liu, M. Huang, R Shi, and X. Wang,"Depth-aware saliency
detection using convolutional neural networks",Journal of Visual
Communication and Image Representation, vol.61, pp.1-9, May. 2019.
•G. Li, Z. Liu, and X. Zhou,"Effective Online Refinement for Video
Object Segmentation",Multimedia Tools and Applications, doi:
10.1007/s11042-019-08146-3, Sept. 2019.
•X. Liu, Z. Liu, and Q. Jiao, O. L. Meur and W.-L.
Zhao,"Saliency-aware inter-image color transfer for image
manipulation",Multimedia Tools and Applications, vol.78, pp.21629-21644,
Aug. 2019.
•X. Liu, Z. Liu, X. Zhou and M. Chen,"SALIENCY-GUIDED IMAGE STYLE TRANSFER",ICMEWorkshop, July. 2019.
2018
•X. Zhou, Z. Liu, C. Gong, and W. Liu, “Improving video saliency
detection via localized estimation and spatiotemporal refinement,” IEEE
Transactions on Multimedia, vol. 20, no. 11, pp. 2993-3007, Nov. 2018.
•L. Shen, K. Li, G. Feng, P. An, and Z. Liu, “Efficient intra mode
selection for depth-map coding utilizing spatiotemporal, inter-component
and inter-view correlations in 3D-HEVC,” IEEE Transactions on Image
Processing, vol. 27, no. 9, pp. 4195-4206, Sept. 2018.
•H. Du, Z. Liu, and R. Shi, “Salient object segmentation based on
depth-aware Image layering,” Multimedia Tools and Applications, DOI:
10.1007/s11042-018-6736-4, Sept. 2018.
•Y. Xie, Z. Liu, X. Zhou, W. Liu, and X. Zou, “Video co-segmentation
based on directed graph,” Multimedia Tools and Applications, DOI:
10.1007/s11042-018-6614-0, Aug. 2018.
•X. Zhou, Z. Liu, C. Gong, G. Li, and M. Huang, “Video saliency
detection using deep convolutional neural networks,” Chinese Conference
on Pattern Recognition and Computer Vision (PRCV), Guangzhou, China,
Nov. 2018.
•L. Wu, Z. Liu, and R. Shi, “Multiple kernel boosting based
two-level RGBD image co-segmentation,” IEEE International Conference on
Multimedia Big Data (BigMM), Xi’an, China, Sept. 2018.
•X. Sun, Y. Wang, T. Ren, Z. Liu, Z. Zha, and G. Wu, “Object
trajectory proposal via hierarchical volume grouping,” ACM International
Conference on Multimedia Retrieval (ICMR), Yokohama, Japan, Jun. 2018,
pp. 344-352.
•X. Zhou, Z. Liu, K. Li, and G. Sun, “Video saliency detection via
bagging-based prediction and spatiotemporal propagation,” Journal of
Visual Communication and Image Representation, vol. 51, pp. 131-143,
Feb. 2018.
•L. Ye, Z. Liu, and Y. Wang, “Learning semantic segmentation with
diverse supervision,” IEEE Winter Conference on Applications of Computer
Vision (WACV), Lake Tahoe, USA, Mar. 2018, pp. 1461-1469.
•L. Wu, Z. Liu, H. Song, and O. Le Meur, “RGBD co-saliency detection
via multiple kernel boosting and fusion,” Multimedia Tools and
Applications, vol. 77, no. 16, pp. 21185-21199, Aug. 2018.
•T. Wu, Z. Liu, X. Zhou, and K. Li, “Spatiotemporal salient object
detection by integrating with objectness,” Multimedia Tools and
Applications, vol. 77, no. 15, pp. 19481-19498, Aug. 2018.
•L. Li, Z. Liu, and J. Zhang, “Unsupervised image co-segmentation
via guidance of simple images,” Neurocomputing, vol. 275, pp. 1650-1661,
Jan. 2018.
•J. Ren, Z. Liu, X. Zhou, G. Sun, and C. Bai, “Saliency integration
driven by similar images,” Journal of Visual Communication and Image
Representation, vol. 50, pp. 227-236, Jan. 2018.
2017
•X. Zhang, C. Zhu, H. Wu, Z. Liu, and Y. Xu, “An imbalance compensation
framework for background subtraction,” IEEE Transactions on Multimedia,
vol. 19, no. 11. pp. 2425-2438, Nov. 2017.
•O. Le Meur, A. Coutrot, Z. Liu, P. Rämä, A. Le Roch, and A. Helo,
“Visual attention saccadic models learn to emulate gaze patterns from
childhood to adulthood,” IEEE Transactions on Image Processing, vol. 26,
no. 10, pp. 4777-4789, Oct. 2017.
•H. Song, Z. Liu, H. Du, G. Sun, O. Le Meur, and T. Ren,
“Depth-aware salient object detection and segmentation via multiscale
discriminative saliency fusion and bootstrap learning,” IEEE
Transactions on Image Processing, vol. 26, no. 9, pp. 4204-4216, Sep.
2017.
•L. Ye, Z. Liu, L. Li, L. Shen, C. Bai, and Y. Wang, “Salient object
segmentation via effective integration of saliency and objectness,”
IEEE Transactions on Multimedia, vol. 19, no. 8. pp. 1742-1756, Aug.
2017.
•C. Ge, N. Kasabov, Z. Liu, and J. Yang, “A spiking neural network
model for obstacle avoidance in simulated prosthetic vision,”
Information Sciences, vol. 399, pp. 30-42, Aug. 2017.
•H. Cheng, J. Zhang, Q. Wu, P. An, and Z. Liu, “Stereoscopic visual
saliency prediction based on stereo contrast and stereo focus,” EURASIP
Journal on Image and Video Processing, vol. 2017, article 61, Sep. 2017.
•L. Shen, P. An, and Z. Liu, “Context-adaptive based CU processing for 3D-HEVC,” PLoS One, vol. 12, no. 2, e0171018, Feb. 2017.
•W. Liu, X. Chen, C. Shen, Z. Liu, and J. Yang, “Semi-global
weighted least squares in image filtering,” International Conference on
Computer Vision (ICCV), pp. 5861-5869, Venice, Italy, Oct. 2017.
•J. Chen, C. Bai, L. Huang, Z. Liu, and S. Chen, “Visual saliency
fusion based multi-feature for semantic image retrieval,” Chinese
Conference on Computer Vision (CCCV), pp. 126-136, Tianjin, China, Oct.
2017.
•T. Maugey, O. Le Meur, and Z. Liu, “Saliency-based navigation in
omnidirectional image,” IEEE International Workshop on Multimedia Signal
Processing (MMSP), pp. 1-6, London-Luton, U.K., Oct. 2017.
•L. Ye, Z. Liu, and Y. Wang, “Depth-aware object instance
segmentation,” International Conference on Image Processing (ICIP), pp.
325-329, Beijing, Sep. 2017.
•O. Le Meur, A. Coutrot, A. Le Roch, A. Helo, P. Rama, and Z. Liu,
“Age-dependent saccadic models for predicting eye movements,”
International Conference on Image Processing (ICIP), pp. 3740-3744,
Beijing, Sep. 2017.
•W. Shan, G. Sun, X. Zhou, and Z. Liu, “Two-stage transfer learning
of end-to-end convolutional neural networks for webpage saliency
prediction,” International Conference on Intelligence Science and Big
Data Engineering (IScIDE), pp. 316-324, Dalian, China, Sep. 2017.
•G. Sun, J. Ren, Z. Liu, and W. Shan, “Two-stage saliency fusion for
object segmentation,” International Conference on Image and Graphics
(ICIG), pp. 139-148, Shanghai, China, Sep. 2017.
•O. Le Meur, A. Coutrot, Z. Liu, A. Le Roch, A. Helo, and P. Rama,
“Your gaze betrays your age,” European Signal Processing Conference
(EUSIPCO), pp. 1942-1946, Kos Island, Greece, Aug. 2017.
2016
•H. Song, Z. Liu, Y. Xie, L. Wu, and M. Huang, “RGBD co-saliency
detection via bagging-based clustering,” IEEE Signal Processing Letters,
vol. 23, no. 12, pp. 1722-1726, Dec. 2016.
•H. Du, Z. Liu, H. Song, L. Mei and Z. Xu, “Improving RGBD saliency
detection using progressive region classification and saliency fusion,”
IEEE Access, vol. 4, pp. 8987-8994, Dec. 2016.
•X. Zhou, Z. Liu, G. Sun, and X. Wang, “Adaptive saliency fusion
based on quality assessment,” Multimedia Tools and Applications, DOI:
10.1007/s11042-016-4093-8, Nov. 2016.
•X. Wang, Y. Zhao, Z. Liu, Y. Jin, and X. Zhu, “Multi-scale deep
residual networks for fine-grained image classification,” International
Forum of Digital TV and Wireless Multimedia Communication, pp. 205-217,
Shanghai, China, Nov. 2016.
•W. Shan, G. Sun, and Z. Liu, “Webpage image saliency prediction via
adaptive SVM,” International Forum of Digital TV and Wireless
Multimedia Communication, pp. 128-136, Shanghai, China, Nov. 2016.
•X. Geng, L. Shen, P. An, and Z. Liu, “Using independent component
analysis and binocular combination for stereoscopic image quality
assessment,” IEEE Visual Communications and Image Processing (VCIP)
Conference, pp. 1-4, Chengdu, China, Nov. 2016.
•L. Shen, Q. Hu, Z. Liu, and P. An, “A new rate control algorithm
based on region of interest for HEVC,” Pacific-Rim Conference on
Multimedia (PCM), Part II, LNCS 9917, pp. 571-579, Xi’an, China, Sep.
2016.
•Z. Liu, J. Li, L. Ye, G. Sun, and L. Shen, “Saliency detection for
unconstrained videos using superpixel-level graph and spatiotemporal
propagation,” IEEE Transactions on Circuits and Systems for Video
Technology, doi.: 10.1109/TCSVT.2016.2595324, Jul. 2016.
•G. Sun, Y. Dong, X. Zhou, and Z. Liu, “Facial descriptor for
Kinect depth using inner–inter-normal components local binary patterns
and tensor histograms,” Machine Vision and Applications, doi.:
10.1007/s00138-016-0783-5, Jun. 2016.
•L. Ye, Z. Liu, X. Zhou, L. Shen, and J. Zhang, “Saliency detection
via similar image retrieval,” IEEE Signal Processing Letters, vol. 23,
no. 6, pp. 838-842, Jun. 2016.
•X. Zhou, Z. Liu, G. Sun, L. Ye, and X. Wang, “Improving saliency
detection via multiple kernel boosting and adaptive fusion,” IEEE Signal
Processing Letters, vol. 23, no. 4, pp. 517-521, Apr. 2016.
•H. Song, Z. Liu, H. Du, and G. Sun, “Depth-aware saliency
detection using discriminative saliency fusion,” IEEE International
Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.
1626-1630, Shanghai, China, Mar. 2016.
2015
• W.Zou, Z.Liu, K.Kpalma, J.Ronsin, Y.Zhao, and N. Komodakis,
“Unsupervised joint salient region detection and object segmentation,”
IEEE Transactions on Image Processing, vol.24, no.11, pp.3858-3873,
Nov.2015.
• L.Ye, Z.Liu, J.Li, W.Zhao and L.Shen, “Co-saliency detection via
co-salient object discovery and recovery,” IEEE Signal Processing
Letters, vol.22,no.11,pp.2073-2077, Nov.2015.
•Z. Liu, O. Le Meur, A. Borji and H. Li, “Special issue on recent
advances in saliency models, applications and evaluations,” Signal
Processing: Image Communication, vol. 38, pp. 1-2, Oct. 2015.
•H. Song, Z. Liu, H. Du, G. Sun, and C. Bai, “Saliency detection
for RGBD images,” International Conference on Internet Multimedia
Computing and Service (ICIMCS), article no. 72, Zhangjiajie, China, Aug.
2015.
•L. Ye, Z. Liu, and L. Li, “Evaluation on fusion of saliency and
objectness for salient object segmentation,” International Conference on
Internet Multimedia Computing and Service (ICIMCS), article no. 18,
Zhangjiajie, China, Aug. 2015.
•X. Fan, Z. Liu, and L. Ye, “Salient object segmentation from
stereoscopic images,” 10th IAPR-TC15 Workshop on Graph-based
Representation in Pattern Recognition (GbRPR), pp. 272-281, Beijing, May
2015.
• Y. Li, K. Fu, Z. Liu, and J. Yang, “Efficient
saliency-model-guided visual co-saliency detection,” IEEE Signal
Processing Letters, vol. 22, no. 5, pp. 588-592, May 2015.
• J. Li, Z. Liu, X. Zhang, O. Le Meur, and L. Shen, “Spatiotemporal
saliency detection based on superpixel-level trajectory,” Signal
Processing: Image Communication, vol. 38, pp. 100-114, Oct. 2015.
• L. Shen, Z. Zhang, X. Zhang, P. An, and Z. Liu, “Fast TU size
decision algorithm for HEVC encoders using Bayesian theorem detection,”
Signal Processing: Image Communication, vol. 32, pp. 121-128, Mar. 2015.
• O. Le Meur, and Z. Liu, “Saccadic model of eye movements for
free-viewing condition,” Vision Research, vol. 116, part B, pp. 152-164,
Nov. 2015.
• C. Bai, J. Zhang, Z. Liu, and W. Zhao, “K-means based histogram
using multiresolution feature vectors for color texture database
retrieval,” Multimedia Tools and Applications, vol. 74, no. 4, pp.
1469-1488, Feb. 2015.
2014
• O. Le Meur, and Z. Liu, “Saliency aggregation: Does unity make
strength?,” Asian Conference on Computer Vision (ACCV), Singapore, Nov.
2014.
• G. Sun, and Z. Liu, “Robust blurred face recognition using
sample-wise kernel estimation and random compressed multi-scale local
binary pattern histograms,” International Conference on Image Processing
(ICIP), pp. 333-337, Paris, Oct. 2014.
• L. Shen, Z. Zhang, and Z. Liu, “Effective CU size decision for
HEVC intracoding,” IEEE Transactions on Image Processing, vol. 23, no.
10, pp. 4232-4241, Oct. 2014.
• L. Shen, Z. Zhang, and Z. Liu, “Adaptive inter-mode decision for
HEVC jointly utilizing inter-level and spatiotemporal correlations,”
IEEE Transactions on Circuits and Systems for Video Technology, vol. 24,
no. 10, pp. 1709-1722, Oct. 2014.
• Z. Liu, X. Zhang, S. Luo, and O. Le Meur, “Superpixel-based
spatiotemporal saliency detection,” IEEE Transactions on Circuits and
Systems for Video Technology, vol. 24, no. 9, pp. 1522-1540, Sep. 2014.
• X. Fan, Z. Liu, and G. Sun, "Salient region detection for
stereoscopic images," International Conference on Digital Signal
Processing (DSP), pp. 454-458, Hong Kong, Aug. 2014.
• X. Zhang, Z. Liu, H. Li, X. Zhao, and P. Zhang, “Statistical
background subtraction based on imbalanced learning,” International
Conference on Multimedia and Expo (ICME), pp. 1-6, Chengdu, Jul. 2014.
• L. Li, Z. Liu, W. Zou, X. Zhang, and O. Le Meur, “Co-saliency
detection based on region-level fusion and pixel-level refinement,”
International Conference on Multimedia and Expo (ICME), pp. 1-6,
Chengdu, Jul. 2014.
• Z. Liu, W. Zou, and O. Le Meur, “Saliency tree: A novel saliency
detection framework,” IEEE Transactions on Image Processing, vol. 23,
no. 5, pp. 1937-1952, May 2014.
• L. Shen, P. An, Z. Liu, and Z. Zhang, “Low complexity depth coding
assisted by coding information from color video,” IEEE Transactions on
Broadcasting, vol. 60, no. 1, pp. 128-133, Mar. 2014.
• Z. Liu, W. Zou, L. Li, L. Shen, and O. Le Meur, “Co-saliency
detection based on hierarchical segmentation,” IEEE Signal Processing
Letters, vol. 21, no. 1, pp. 88-92, Jan. 2014.
2013
• W. Zou, K. Kpalma, Z. Liu, and J. Ronsin, “Segmentation driven
low-rank matrix recovery for saliency detection,” British Machine Vision
Conference (BMVC), Bristol, United Kingdom, article 79, Sep. 2013.
• X. Zhang, J. Cheng, Z. Liu, and J. Yang, “Cost-sensitive
background subtraction,” International Conference on Image Processing
(ICIP), Melbourne, Australia, pp. 3336-3339, Sep. 2013.
• Z. Liu, O. Le Meur, and S. Luo, “Superpixel-based saliency
detection,” International Workshop on Image and Audio Analysis for
Multimedia Interactive Services (WIAMIS), Paris, France, article
6616119, Jul. 2013.
• H. Du, Z. Liu, J. Jiang, and L. Shen, “Stretchability-aware block
scaling for image retargeting,” Journal of Visual Communication and
Image Representation, vol. 24, no. 4, pp. 499-508, May 2013.
• L. Zha, Z. Liu, S. Luo, and L. Shen, “A novel region merging based
image segmentation approach for automatic object extraction,” IEEE
International Symposium on Circuits and Systems (ISCAS), Beijing, China,
pp. 970-973, 19-23 May 2013.
• L. Shen, Z. Liu, and Z. Zhang, “A novel H.264 rate control
algorithm with consideration of visual attention,” Multimedia Tools and
Applications, vol. 63, no. 3, pp. 709-727, Apr. 2013.
• Z. Liu, O. Le Meur, S. Luo, and L. Shen, “Saliency detection using
regional histograms,” Optics Letters, vol. 38, no. 5, pp. 700-702, Mar.
2013.
• L. Shen, Z. Liu, X. Zhang, W. Zhao, and Z. Zhang, “An effective CU
size decision method for HEVC encoders,” IEEE Transactions on
Multimedia, vol. 15, no. 2. pp. 465-470, Feb. 2013.
2012
• Z. Liu, R. Shi, L. Shen, Y. Xue, K. N. Ngan, and Z. Zhang,
“Unsupervised salient object segmentation based on kernel density
estimation and two-phase graph cut,” IEEE Transactions on Multimedia,
vol. 14, no. 4, pp. 1275-1289, Aug. 2012.
• L. Shen, Z. Zhang, and Z. Liu, “Inter mode selection for depth map
coding in 3D video,” IEEE Transactions on Consumer Electronics, vol.
58, no. 3, pp. 926-931, Aug. 2012.
• R. Shi, Z. Liu, H. Du, X. Zhang, and L. Shen, “Region diversity
maximization for salient object detection,” IEEE Signal Processing
Letters, vol. 19, no. 4, pp. 215–218, Apr. 2012.
2011
• R. Shi, Z. Liu, Y. Xue, and X. Zhang, “Interactive object segmentation
using iterative adjustable graph cut,” Visual Communications and Image
Processing (VCIP) Conference, Tainan, Taiwan, Nov. 2011.
• L. Shen, Z. Liu, P. An, R. Ma, and Z. Zhang, “Low-complexity mode
decision for MVC,” IEEE Transactions on Circuits and Systems for Video
Technology, vol. 21, no. 6, pp. 837-843, Jun. 2011.
• Y. Xue, Z. Liu, and Shi Ran, “Saliency detection using multiple
region-based features,” Optical Engineering, vol. 50, no. 5, pp. 057008,
May 2011.
• Z. Liu, Y. Xue, H. Yan, and Z. Zhang, “Efficient saliency
detection based on Gaussian models,” IET Image Processing, vol. 5, no.
2, pp. 122-131, Mar. 2011.
• Z. Liu, L. Shen, and Z. Zhang, “Unsupervised image segmentation
based on analysis of binary partition tree for salient object
extraction,” Signal Processing, vol. 91, no. 2, pp. 290-299, Feb. 2011.
2010
• R. Shi, Z. Liu, Y. Xue, “Salient object segmentation based on graph
cut,” International Symposium on Intelligent Signal Processing and
Communications Systems (ISPACS), Chengdu, China, pp. 321-324, Dec. 2010.
• X. Zhang, Z. Liu, J. Yang, “Moving object segmentation based on
new likelihood functions”, International Symposium on Intelligent Signal
Processing and Communications Systems (ISPACS), Chengdu, China, pp.
313-316, Dec. 2010.
• L. Shen, Y. Sun, Z. Liu, and Z. Zhang, “Efficient SKIP mode
detection for coarse grain quality scalable video coding,” IEEE Signal
Processing Letters, vol. 17, no. 10, pp. 887-890, Oct. 2010.
• Z. Liu, Y. Xue, L. Shen, and Z. Zhang, “Nonparametric saliency
detection using kernel density estimation,” International Conference on
Image Processing (ICIP), Hong Kong, pp. 253-256, Sept. 2010.
• L. Shen, Z. Liu, P. An, R. Ma, and Z. Zhang, “An adaptive early
termination of mode decision using inter-layer correlation in scalable
video coding,” International Conference on Image Processing (ICIP), Hong
Kong, pp. 4229-4232, Sept. 2010.
• L. Shen, Z. Liu, P. An, R. Ma, and Z. Zhang, “Fast mode decision
for scalable video coding utilizing spatial and interlayer correlation,”
Journal of Electronic Imaging, vol. 19, no. 3, pp. 033010, Aug. 2010.
• Z. Liu, L. Wang, L. Shen, and Z. Zhang, “Unsupervised salient
object segmentation from color images,” SPIE Conference on Visual
Communications and Image Processing (VCIP), Huangshan, China, pp.
77441Q, Jul. 2010.
• L. Shen, Z. Liu, T. Yan, Z. Zhang, and P. An, “View-adaptive
motion estimation and disparity estimation for low complexity multiview
video coding,” IEEE Transactions on Circuits and Systems for Video
Technology, vol. 20, no. 6, pp. 925-930, Jun. 2010.
• Z. Liu, W. Li, L. Shen, Z. Han, and Z. Zhang, “Automatic
segmentation of focused objects from images with low depth of field,”
Pattern Recognition Letters, vol. 31, no. 7, pp. 572-581, May 2010.
• L. Shen, Z. Liu, T. Yan, Z. Zhang, and P. An, “Early SKIP mode
decision for MVC using inter-view correlation,” Signal Processing: Image
Communication, vol. 25, no. 2, pp. 88-93, Feb. 2010.
• Z. Liu, H. Yan, L. Shen, K. Ngan, and Z. Zhang, “Adaptive image
retargeting using saliency-based continuous seam carving,” Optical
Engineering, vol. 49, no. 1, pp. 017002, Jan. 2010.
2009
• L. Shen, Z. Liu, S. Liu, Z. Zhang, and P. An, “Selective disparity
estimation and variable size motion estimation based on motion
homogeneity for multi-view coding,” IEEE Transactions on Broadcasting,
vol. 55, no. 4, pp. 761-766, Dec. 2009.
• L. Shen, T. Yan, Z. Liu, Z. Zhang, P. An, and L. Yang, “Fast mode
decision for multiview video coding,” International Conference on Image
Processing (ICIP),Cairo, Egypt, pp. 2953-2956, Nov. 2009.
• X. Zhang, J. Yang, and Z. Liu, “Foreground segmentation based on
tracking,” Optical Engineering, vol. 48, no. 10, pp. 107203, Oct. 2009.
• L. Shen, G. Feng, Z. Liu, Z. Zhang, and P. An, “Macroblock-level
adaptive search range algorithm for motion estimation in multiview video
coding,” Journal of Electronic Imaging, vol. 18, no. 3, pp. 033003,
Jul. 2009.
• Z. Liu, H. Yan, L. Shen, Y. Wang, and Z. Zhang, “A motion
attention model based rate control algorithm for H.264/AVC,” IEEE/ACIS
International Conference on Computer and Information Science (ICIS),
Shanghai, China, pp. 568-573, Jun. 2009.
• Z. Han, Z. Liu, Z. Zhang, Y. Lu, W. Li, and H. Yan, “Salient
object extraction based on region saliency ratio,” IEEE/ACIS
International Conference on Computer and Information Science (ICIS),
Shanghai, China, pp. 611-615, Jun. 2009.
• L. Shen, Z. Liu, Z. Zhang, and X. Shi, “Selective VS-MRF-ME and
intra coding in H.264 based on spatiotemporal continuity of motion
field,” Signal Processing: Image Communication, vol. 24, no. 5, pp.
405-414, May 2009.
• X. Zhang, J. Yang, and Z. Liu, “Performance evaluation of
foreground modeling in moving foreground segmentation,” Optical
Engineering, vol. 48, no. 3, pp. 030505, Mar. 2009.
• Z. Liu, L. Shen, and Z. Zhang, “An efficient intermode decision
algorithm based on motion homogeneity for H.264/AVC,” IEEE Transactions
on Circuits and Systems for Video Technology, vol. 19, no. 1, pp.
128-132, Jan. 2009.
• L. Shen, Z. Liu, Z. Zhang, and X. Shi, “Frame-level bit allocation
based on incremental PID algorithm and frame complexity estimation,”
Journal of Visual Communication and Image Representation, vol. 20, no.
1, pp. 28-34, Jan. 2009.
2008
• L. Shen, Z. Liu, and Z. Zhang, “Fast multiframe selection algorithm
based on spatial-temporal characteristics of motion field,” Journal of
Electronic Imaging, vol. 17, no. 4, pp. 043004, Dec. 2008.
• L. Shen, Z. Liu, Z. Zhang, and X. Shi, “Fast inter mode decision
using spatial property of motion field,” IEEE Transactions on
Multimedia, vol. 10, no. 6, pp. 1208-1214, Oct. 2008.
• Z. Liu, W. Li, X. Zhang, and J. Yang, “Efficient face segmentation
based on face attention model and seeded region merging,” International
Conference on Signal Processing (ICSP), Beijing, China, vol. 2, pp.
1116-1119, Oct. 2008.
• Z. Liu, J. Gu, L. Shen, Z. Zhang, “Efficient video object
segmentation based on Gaussian mixture model and Markov random field”,
International Conference on Signal Processing (ICSP), Beijing, China,
vol. 2, pp. 1006-1009, Oct. 2008.
• X. Zhang, J. Yang, Z. Liu, and X. Wang, “Segmenting foreground
from similarly colored background,” Optical Engineering, vol. 47, no. 7,
pp. 077002, Jul. 2008.
• L. Shen, Z. Liu, Z. Zhang, L. Wang, and G. Wang, “Novel intermode
decision algorithm in H.264/AVC,” Journal of Electronic Imaging, vol.
17, no. 1, pp. 013006, Mar. 2008.
2007
• L. Shen, Z. Liu, Z. Zhang, and G. Wang, “An adaptive and fast
multiframe selection algorithm for H.264 video coding,” IEEE Signal
Processing Letters, vol. 14, no. 11, pp. 836-839, Nov. 2007.
• L. Shen, Z. Zhang, Z. Liu, and W. Zhang, “An adaptive and fast
fractional pixel search algorithm in H.264,” Signal Processing, vol. 87,
no. 11, pp. 2629-2639, Nov. 2007.
• Z. Liu, L. Shen, Z. Han, and Z. Zhang, “A novel video object
tracking approach based on kernel density estimation and Markov random
field,” International Conference on Image Processing (ICIP), San
Antonio, USA, vol. 3, pp. 373-376, Sept. 2007.
• L. Shen, Z. Liu, Z. Zhang, and X. Shi, “An adaptive and fast H.264
multi-frame selection algorithm based on information from previous
searches”, International Conference on Multimedia Expo (ICME), pp.
1591-1594, Beijing, Jul. 2007.
• L. Shen, Z. Liu, Z. Zhang, and X. Shi, “Rate control based on
incremental Proportional-Integral-Differential algorithm,” Optical
Engineering, vol. 46, no. 7, pp. 077002, Jul. 2007.
• Z. Liu, Y. Lu, and Z. Zhang, “Real-time spatiotemporal
segmentation of video objects in the H.264 compressed domain,” Journal
of Visual Communication and Image Representation, vol. 18, no. 3, pp.
275-290, Jun. 2007.
• Z. Liu, Z. Zhang, and L. Shen, “Moving object segmentation in the
H.264 compressed domain,” Optical Engineering, vol. 46, no. 1, pp.
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2006
• Z. Liu, L. Shen, and Z. Zhang, “Automatic video object segmentation
from MPEG compressed domain”, International Workshop on Image Analysis
for Multimedia Interactive Services (WIAMIS), Incheon, Korea, pp.
333-336, Apr. 2006.
2005
• N. Peng, J. Yang, and Z. Liu, “Performance analysis for tracking of
variable scale objects using mean-shift algorithm,” Optical Engineering,
vol. 44, no. 7, pp. 070505, Jul. 2005.
• Z. Liu, J. Yang, and N. Peng, “An efficient face segmentation
algorithm based on binary partition tree,” Signal Processing: Image
Communication, vol. 20, no. 4, pp. 295-314, Apr. 2005.
• Z. Liu, J. Yang, and N. Peng, “Semi-automatic video object
segmentation using seeded region merging and bidirectional projection,”
Pattern Recognition Letters, vol. 26, no. 5, pp. 653-662, Apr. 2005.
• N. Peng, J. Yang, and Z. Liu, “Mean shift blob tracking with
kernel histogram filtering and hypothesis testing,” Pattern Recognition
Letters, vol. 26, no. 5, pp. 605-614, Apr. 2005.
2004
• Z. Liu, and J. Yang, “Interactive video object segmentation: Fast
seeded region merging approach,” Electronics Letters, vol. 40, no. 5,
pp. 302-304, Mar. 2004.