Institution
Harbin Institute of Technology
Education•Harbin, China•
About: Harbin Institute of Technology is a education organization based out in Harbin, China. It is known for research contribution in the topics: Microstructure & Control theory. The organization has 88259 authors who have published 109297 publications receiving 1603393 citations. The organization is also known as: HIT.
Topics: Microstructure, Control theory, Ultimate tensile strength, Alloy, Laser
Papers published on a yearly basis
Papers
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08 Sep 2018TL;DR: A special shift-connection layer to the U-Net architecture, namely Shift-Net, is introduced for filling in missing regions of any shape with sharp structures and fine-detailed textures and an end-to-end learning algorithm is further developed to train the Shift- net.
Abstract: Deep convolutional networks (CNNs) have exhibited their potential in image inpainting for producing plausible results. However, in most existing methods, e.g., context encoder, the missing parts are predicted by propagating the surrounding convolutional features through a fully connected layer, which intends to produce semantically plausible but blurry result. In this paper, we introduce a special shift-connection layer to the U-Net architecture, namely Shift-Net, for filling in missing regions of any shape with sharp structures and fine-detailed textures. To this end, the encoder feature of the known region is shifted to serve as an estimation of the missing parts. A guidance loss is introduced on decoder feature to minimize the distance between the decoder feature after fully connected layer and the ground-truth encoder feature of the missing parts. With such constraint, the decoder feature in missing region can be used to guide the shift of encoder feature in known region. An end-to-end learning algorithm is further developed to train the Shift-Net. Experiments on the Paris StreetView and Places datasets demonstrate the efficiency and effectiveness of our Shift-Net in producing sharper, fine-detailed, and visually plausible results. The codes and pre-trained models are available at https://github.com/Zhaoyi-Yan/Shift-Net.
360 citations
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14 Jun 2020
TL;DR: SiamBAN views the visual tracking problem as a parallel classification and regression problem, and thus directly classifies objects and regresses their bounding boxes in a unified FCN, making SiamB Ban more flexible and general.
Abstract: Most of the existing trackers usually rely on either a multi-scale searching scheme or pre-defined anchor boxes to accurately estimate the scale and aspect ratio of a target. Unfortunately, they typically call for tedious and heuristic configurations. To address this issue, we propose a simple yet effective visual tracking framework (named Siamese Box Adaptive Network, SiamBAN) by exploiting the expressive power of the fully convolutional network (FCN). SiamBAN views the visual tracking problem as a parallel classification and regression problem, and thus directly classifies objects and regresses their bounding boxes in a unified FCN. The no-prior box design avoids hyper-parameters associated with the candidate boxes, making SiamBAN more flexible and general. Extensive experiments on visual tracking benchmarks including VOT2018, VOT2019, OTB100, NFS, UAV123, and LaSOT demonstrate that SiamBAN achieves state-of-the-art performance and runs at 40 FPS, confirming its effectiveness and efficiency. The code will be available at https://github.com/hqucv/siamban.
358 citations
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TL;DR: A comprehensive review of the progress in biomass torrefaction technologies is provided in this article, where the authors perform an in-depth literature survey and identify a current trend in practical tor-refaction development and environmental performance.
357 citations
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TL;DR: In this article, a giant electrocaloric effect (ECE) near room temperature is reported in a lead-free bulk inorganic material, which exhibits relaxor ferroelectric response to near the invariant critical point.
Abstract: A giant electrocaloric effect (ECE) near room temperature is reported in a lead-free bulk inorganic material. By tuning Ba(ZrxTi1–x)O3 compositions which also exhibit relaxor ferroelectric response to near the invariant critical point, the Ba(ZrxTi1–x)O3 bulk ceramics at x ∼ 0.2 exhibit a large adiabatic temperature drop of 4.5 K, a large isothermal entropy change of 8 J kg−1 K−1, and a large EC coefficient (|ΔTc/ΔE| = 0.52 × 10−6 KmV−1 and ΔS/ΔE = 0.93 × 10−6 J m kg−1 K−1 V−1) over a 30 K temperature range. These properties added together indicate a general solution of the electrocaloric materials with high performance for practical cooling applications.
357 citations
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15 Jun 2019TL;DR: In this paper, an iterative kernel correction (IKC) method was proposed for blur kernel estimation in blind super-resolution (SR) problem, where the blur kernels are unknown and the kernel mismatch could bring regular artifacts (either over-sharpening or over-smoothing), which can be applied to correct inaccurate blur kernels.
Abstract: Deep learning based methods have dominated super-resolution (SR) field due to their remarkable performance in terms of effectiveness and efficiency. Most of these methods assume that the blur kernel during downsampling is predefined/known (e.g., bicubic). However, the blur kernels involved in real applications are complicated and unknown, resulting in severe performance drop for the advanced SR methods. In this paper, we propose an Iterative Kernel Correction (IKC) method for blur kernel estimation in blind SR problem, where the blur kernels are unknown. We draw the observation that kernel mismatch could bring regular artifacts (either over-sharpening or over-smoothing), which can be applied to correct inaccurate blur kernels. Thus we introduce an iterative correction scheme -- IKC that achieves better results than direct kernel estimation. We further propose an effective SR network architecture using spatial feature transform (SFT) layers to handle multiple blur kernels, named SFTMD. Extensive experiments on synthetic and real-world images show that the proposed IKC method with SFTMD can provide visually favorable SR results and the state-of-the-art performance in blind SR problem.
357 citations
Authors
Showing all 89023 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jiaguo Yu | 178 | 730 | 113300 |
Lei Jiang | 170 | 2244 | 135205 |
Gang Chen | 167 | 3372 | 149819 |
Xiang Zhang | 154 | 1733 | 117576 |
Hui-Ming Cheng | 147 | 880 | 111921 |
Yi Yang | 143 | 2456 | 92268 |
Bruce E. Logan | 140 | 591 | 77351 |
Bin Liu | 138 | 2181 | 87085 |
Peng Shi | 137 | 1371 | 65195 |
Hui Li | 135 | 2982 | 105903 |
Lei Zhang | 135 | 2240 | 99365 |
Jie Liu | 131 | 1531 | 68891 |
Lei Zhang | 130 | 2312 | 86950 |
Zhen Li | 127 | 1712 | 71351 |
Kurunthachalam Kannan | 126 | 820 | 59886 |