Search

Your search keyword '"Liu, Dingming"' showing total 102 results
Start Over Author "Liu, Dingming"
102 results on '"Liu, Dingming"'

1. ConCLVD: Controllable Chinese Landscape Video Generation via Diffusion Model

Author

Liu, Dingming, Li, Shaowei, Zhou, Ruoyan, Liang, Lili, Hong, Yongguan, Chao, Fei, and Ji, Rongrong

Subjects
Computer Science - Multimedia
Abstract

Chinese landscape painting is a gem of Chinese cultural and artistic heritage that showcases the splendor of nature through the deep observations and imaginations of its painters. Limited by traditional techniques, these artworks were confined to static imagery in ancient times, leaving the dynamism of landscapes and the subtleties of artistic sentiment to the viewer's imagination. Recently, emerging text-to-video (T2V) diffusion methods have shown significant promise in video generation, providing hope for the creation of dynamic Chinese landscape paintings. However, challenges such as the lack of specific datasets, the intricacy of artistic styles, and the creation of extensive, high-quality videos pose difficulties for these models in generating Chinese landscape painting videos. In this paper, we propose CLV-HD (Chinese Landscape Video-High Definition), a novel T2V dataset for Chinese landscape painting videos, and ConCLVD (Controllable Chinese Landscape Video Diffusion), a T2V model that utilizes Stable Diffusion. Specifically, we present a motion module featuring a dual attention mechanism to capture the dynamic transformations of landscape imageries, alongside a noise adapter to leverage unsupervised contrastive learning in the latent space. Following the generation of keyframes, we employ optical flow for frame interpolation to enhance video smoothness. Our method not only retains the essence of the landscape painting imageries but also achieves dynamic transitions, significantly advancing the field of artistic video generation. The source code and dataset are available at https://anonymous.4open.science/r/ConCLVD-EFE3.

Published
2024

2. Quality-Aware CLIP for Blind Image Quality Assessment

Author

Pan, Wensheng, Yang, Zhifu, Liu, DingMing, Fang, Chenxin, Zhang, Yan, Dai, Pingyang, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Liu, Qingshan, editor, Wang, Hanzi, editor, Ma, Zhanyu, editor, Zheng, Weishi, editor, Zha, Hongbin, editor, Chen, Xilin, editor, Wang, Liang, editor, and Ji, Rongrong, editor

Published
2024
Full Text
View/download PDF

11. Multi-objective Evolutionary Instance Selection for Multi-label Classification

Author

Liu, Dingming, Shang, Haopu, Hong, Wenjing, Qian, Chao, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Khanna, Sankalp, editor, Cao, Jian, editor, Bai, Quan, editor, and Xu, Guandong, editor

Published
2022
Full Text
View/download PDF

14. Personalized Tour Itinerary Recommendation Algorithm Based on Tourist Comprehensive Satisfaction.

Author

Liu, Dingming, Wang, Lizheng, Zhong, Yanling, Dong, Yi, and Kong, Jinling

Subjects
SATISFACTION, TOURISTS, ALGORITHMS, TOURS, APPROXIMATION algorithms
Abstract

Personalized travel itinerary recommendation algorithms are the focus of research in smart tourism and tourism GIS. Aiming to address issues present in travel itinerary recommendations for the increasingly popular "self-drive tour" mode, this study proposes an algorithm based on comprehensive tourist satisfaction to mitigate problems such as the neglect of important relevant factors and low degree of personalization. First, we construct a model of tourist satisfaction for travel itineraries by comprehensively considering factors including time utilization, the attractiveness of attractions, itinerary feasibility, and the diversity of attraction types. Unlike previous studies, we consider dining and accommodation time during the itinerary, the physical condition of tourists, and the diversity of attraction types, and establish penalty functions to flexibly constrain deviations from the expected conditions in itinerary planning. Then, with the optimization of comprehensive tourist satisfaction as the objective, we design a new algorithm to address the itinerary recommendation problem, supporting tourists in selecting must-visit attractions, restaurants, and hotels, as well as personalized preferences such as the sightseeing sequence. The experimental results demonstrate that our proposed algorithm outperforms two baseline algorithms, providing higher comprehensive tourist satisfaction while also exhibiting greater feasibility in itinerary planning. The proposed algorithm effectively addresses the issue of personalized travel itinerary recommendation, presenting an efficient, feasible, and practical solution. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

30. Novel Local Particle Swarm Optimizer for Multi-modal Optimization

Author

Jiao, Yuechao, Yang, Lei, Qu, Boyang, Liu, Dingming, Liang, J. J., Xiao, Junming, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Tan, Ying, editor, Shi, Yuhui, editor, and Niu, Ben, editor

Published
2016
Full Text
View/download PDF

39. Deformation behavior of a TiZr-based metallic glass composite containing dendrites in the supercooled liquid region

Author

Zhang Hong-Wei, Li Zhengkun, Li Hong, Liu Dingming, Zhang Long, Zhang Haifeng, Wang Ai-min, Hua-meng Fu, Zhu Zhengwang, and Wu Longjun

Subjects
Materials science, Amorphous metal, Polymers and Plastics, Mechanical Engineering, Metals and Alloys, Superplasticity, 02 engineering and technology, Work hardening, 010402 general chemistry, 021001 nanoscience & nanotechnology, 01 natural sciences, 0104 chemical sciences, law.invention, Dendrite (crystal), Mechanics of Materials, law, Materials Chemistry, Ceramics and Composites, Formability, Crystallization, Deformation (engineering), Composite material, 0210 nano-technology, Supercooling
Abstract

The deformation behavior of a TiZr-based bulk metallic glass composite (BMGC) was characterized in the supercooled liquid region (SLR) from 623 K to 693 K. It was observed that the alloy exhibits the deformation behavior from work softening at low temperatures to work hardening at high temperatures. The yield stress and overshoot stress decrease remarkably with the increase of temperature, accompanied by superplasticity. The results showed that the crystallization occurred in the amorphous matrix for the post-deformation samples and the volume fraction of the corresponding crystallization products increased with increasing testing temperature. It is implied that the work hardening behavior was closely associated with the crystallization of the amorphous matrix. The tensile stress can accelerate the crystallization of amorphous matrix and the martensitic transformation of dendrite phases, which implies that the thermal stability of the alloy decreases under tension. These findings shed light on designing new BMGCs with high mechanical performance as well as the good SLR formability.

Published
2020

44. How does government spending news affect interest rates? Evidence from the United States

Author

Chen Yong and Liu Dingming

Subjects
Government spending, Economics and Econometrics, 050208 finance, Control and Optimization, Applied Mathematics, media_common.quotation_subject, 05 social sciences, Monetary policy, Variance (accounting), Monetary economics, Affect (psychology), Interest rate, Term (time), Surprise, Shock (economics), 0502 economics and business, Economics, 050207 economics, media_common
Abstract

This study analyzes the effects of news shocks to U.S. government spending on interest rates, especially long-term interest rates, and investigates the role of agents’ expectations in the propagation of government spending to interest rates. Using large Bayesian vector autoregressive models with sufficient information, we find that news about increases in government spending induce significant increases in both short- and long-term interest rates while the effects of government spending surprise shocks on interest rates are mixed and ambiguous. Government spending news shocks in the baseline model account for around 10% of the variance in forecast errors in long-term interest rates, which is much more important than government spending itself. Using empirical dynamic term structural models, we further decompose increases in long-term interest rates into changes in expectations of future monetary policy and changes in term premiums. We find that an increase in the long-term interest rate after a positive government spending news shock mainly reflects higher expected future short-term interest rates, which demonstrates the importance of the coordination between fiscal and monetary policy communication.

Published
2019

49. Foreign official purchases of U.S. treasuries and mortgage rates.

Author

Fang, Jing and Liu, Dingming

Subjects
MORTGAGE rates, FOREIGN exchange, MECHANICAL shock measurement, PURCHASING, IMPULSE response
Abstract

This paper investigates the effects of foreign official purchases of U.S. treasuries on mortgage rates from January 1985 to June 2007 using a proxy structural vector autoregression (SVAR) model, where shocks to foreign official inflows to treasuries are identified by their correlation with foreign exchange interventions. Although mortgage rates significantly decrease in response to positive shocks to foreign official purchases of U.S. treasuries, these shocks only explain a small fraction of the variation in the U.S. mortgage rate. [ABSTRACT FROM AUTHOR]

Published
2019
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results