作者: 擴(kuò)大 時(shí)間: 2025-3-21 23:29
Donor Selection for Adults and Pediatricsever, is highly challenging due to factors such as variation in human bodies, clothing and viewpoint. Prior methods addressing this problem typically attempt to fit parametric body models with certain priors on pose and shape. In this work we argue for an alternative representation and propose BodyN作者: 不可侵犯 時(shí)間: 2025-3-22 02:26 作者: judicial 時(shí)間: 2025-3-22 04:34
Emma C. Morris,J. H. F. (Fred) Falkenburgocess, and, in many applications, the need for this reasoning process to be . to assist users in both development and prediction. Existing models designed to produce interpretable traces of their decision-making process typically require these traces to be supervised at training time. In this paper,作者: decipher 時(shí)間: 2025-3-22 09:54 作者: 謙卑 時(shí)間: 2025-3-22 15:46
Franck Morschhauser,Pier Luigi Zinzanis explored for more advanced video processing. In this paper, we propose a learnable unified framework for propagating a variety of visual properties of video images, including but not limited to color, high dynamic range (HDR), and segmentation mask, where the properties are available for only a fe作者: 謙卑 時(shí)間: 2025-3-22 18:49
Differential Diagnosis of Pathologic Q waves3D shape as a set of locality-preserving 1D ordered list of points at multiple resolutions. This allows efficient feed-forward processing through 1D convolutions, coarse-to-fine analysis through a multi-grid architecture, and it leads to faster convergence and small memory footprint during training.作者: Yag-Capsulotomy 時(shí)間: 2025-3-22 23:39
Acute and Chronic Pericarditis,ncorporates the body part based structural connectivity of joints to learn the high spatial correlation of human posture on our method. Towards this goal, we propose a new long short-term memory (LSTM)-based deep learning architecture named propagating LSTM networks (p-LSTMs), where each LSTM is con作者: epicardium 時(shí)間: 2025-3-23 04:03 作者: 思考 時(shí)間: 2025-3-23 05:54 作者: bonnet 時(shí)間: 2025-3-23 13:02
https://doi.org/10.1007/978-1-84800-171-8identification (re-ID). To achieve it, we propose a novel Robust AnChor Embedding (RACE) framework via deep feature representation learning for large-scale unsupervised video re-ID. Within this framework, anchor sequences representing different persons are firstly selected to formulate an anchor gra作者: Defiance 時(shí)間: 2025-3-23 17:34 作者: orthopedist 時(shí)間: 2025-3-23 18:28
Acute and Chronic Pericarditis,y Equilibrium Generative Adversarial Network (BEGAN), which is one of the state-of-the-art generative models. Despite its potential of generating high-quality images, we find that BEGAN tends to collapse at some modes after a period of training. We propose a new model, called . (BEGAN-CS), which inc作者: 細(xì)頸瓶 時(shí)間: 2025-3-24 00:19
https://doi.org/10.1007/978-1-84800-171-8ld. Recently, a few domain adaptation and active learning approaches have been proposed to mitigate the performance drop. However, very little attention has been made toward leveraging information in videos which are naturally captured in most camera systems. In this work, we propose to leverage “mo作者: 被詛咒的人 時(shí)間: 2025-3-24 03:55
Acute and Chronic Pericarditis,e underlying body geometry, motion component and the clothing as a geometric layer. So far this clothing layer has only been used as raw offsets for individual applications such as retargeting a different body capture sequence with the clothing layer of another sequence, with limited scope, . using 作者: exquisite 時(shí)間: 2025-3-24 08:09 作者: 有幫助 時(shí)間: 2025-3-24 11:46
https://doi.org/10.1007/978-1-84800-171-8SR are more difficult to train. The low-resolution inputs and features contain abundant low-frequency information, which is treated equally across channels, hence hindering the representational ability of CNNs. To solve these problems, we propose the very deep residual channel attention networks (RC作者: 使隔離 時(shí)間: 2025-3-24 18:28
https://doi.org/10.1007/978-3-030-01234-2computer vision; machine learning; deep neural networks; reinforcement learning; object recognition; imag作者: PANG 時(shí)間: 2025-3-24 21:03 作者: 沙草紙 時(shí)間: 2025-3-25 01:14 作者: Compass 時(shí)間: 2025-3-25 04:50
Computer Vision – ECCV 2018978-3-030-01234-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Cerumen 時(shí)間: 2025-3-25 11:34
Learning to Blend Photosround image and a background image, our proposed method automatically generates a set of blending photos with scores that indicate the aesthetics quality with the proposed quality network and policy network. Experimental results show that the proposed approach can effectively generate high quality blending photos with efficiency.作者: recede 時(shí)間: 2025-3-25 14:40 作者: 許可 時(shí)間: 2025-3-25 18:44
0302-9743 missions. The papers are organized in topical?sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstruction; optimization;?matching and recognition; video attention; and poster sessions..978-3-030-01233-5978-3-030-01234-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Inveterate 時(shí)間: 2025-3-25 23:51 作者: 嘴唇可修剪 時(shí)間: 2025-3-26 04:03 作者: 灰姑娘 時(shí)間: 2025-3-26 06:58 作者: saphenous-vein 時(shí)間: 2025-3-26 10:10
Catherine Rioufol,Christian Wichmann using Cityscapes, COCO, and aerial image datasets, learning to segment objects without ever having seen a mask in training. Our method exceeds the performance of existing weakly supervised methods, without requiring hand-tuned segment proposals, and reaches . of supervised performance.作者: 阻擋 時(shí)間: 2025-3-26 13:01
Differential Diagnosis of Pathologic Q wavesarks, while tree-structured decoders can be used for generating point clouds directly and they outperform existing approaches for image-to-shape inference tasks learned using the ShapeNet dataset. Our model also allows unsupervised learning of point-cloud based shapes by using a variational autoencoder, leading to higher-quality generated shapes.作者: thalamus 時(shí)間: 2025-3-26 16:50
Electrolyte Imbalance and Disturbances,mplementarity between the learned representations in the two branches. HybridNet is able to outperform state-of-the-art results on CIFAR-10, SVHN and STL-10 in various semi-supervised settings. In addition, visualizations and ablation studies validate our contributions and the behavior of the model on both CIFAR-10 and STL-10 datasets.作者: 空氣傳播 時(shí)間: 2025-3-26 23:20
CBAM: Convolutional Block Attention Moduleperiments on ImageNet-1K, MS?COCO detection, and VOC?2007 detection datasets. Our experiments show consistent improvements in classification and detection performances with various models, demonstrating the wide applicability of CBAM. The code and models will be publicly available.作者: 貨物 時(shí)間: 2025-3-27 01:35 作者: misanthrope 時(shí)間: 2025-3-27 05:37 作者: Hallowed 時(shí)間: 2025-3-27 10:39 作者: 起來(lái)了 時(shí)間: 2025-3-27 17:30 作者: 損壞 時(shí)間: 2025-3-27 18:33 作者: Entrancing 時(shí)間: 2025-3-27 23:00
Electrolyte Imbalance and Disturbances,zes 3D pose representation and temporal sequence recognition. Experiments on three benchmark datasets validate the competitive performance of our proposed method, as well as its efficiency and robustness to handle noisy joints of pose.作者: averse 時(shí)間: 2025-3-28 03:29
Acute and Chronic Pericarditis, effect of latent-space constraint. The experimental results show that our method has additional advantages of being able to train on small datasets and to generate images similar to a given real image yet with variations of designated attributes on-the-fly.作者: Robust 時(shí)間: 2025-3-28 08:46 作者: Morose 時(shí)間: 2025-3-28 13:51
Propagating LSTM: 3D Pose Estimation Based on Joint Interdependency about 11.2% than state-of-the-art methods on the largest publicly available database. Importantly, we demonstrate that the JI drastically reduces the structural errors at body edges, thereby leads to a significant improvement.作者: 暗指 時(shí)間: 2025-3-28 18:40 作者: 性學(xué)院 時(shí)間: 2025-3-28 20:30
Escaping from Collapsing Modes in a Constrained Space effect of latent-space constraint. The experimental results show that our method has additional advantages of being able to train on small datasets and to generate images similar to a given real image yet with variations of designated attributes on-the-fly.作者: Digest 時(shí)間: 2025-3-29 01:00 作者: Hay-Fever 時(shí)間: 2025-3-29 04:02
BodyNet: Volumetric Inference of 3D Human Body Shapesut and show state-of-the-art results on the SURREAL and Unite the People datasets, outperforming recent approaches. Besides achieving state-of-the-art performance, our method also enables volumetric body-part segmentation.作者: albuminuria 時(shí)間: 2025-3-29 07:39
Switchable Temporal Propagation Network TPN with bi-directional training on pairs of frames. We apply the switchable TPN to three tasks: colorizing a gray-scale video based on a few colored key-frames, generating an HDR video from a low dynamic range (LDR) video and a few HDR frames, and propagating a segmentation mask from the first fra作者: 不規(guī)則的跳動(dòng) 時(shí)間: 2025-3-29 12:56 作者: 創(chuàng)造性 時(shí)間: 2025-3-29 18:34
Holistic 3D Scene Parsing and Reconstruction from a Single RGB Imageated by our 3D representation, over the space of depth, surface normal, and object segmentation map. The optimal configuration, represented by a parse graph, is inferred using Markov chain Monte Carlo (MCMC), which efficiently traverses through the non-differentiable solution space, jointly optimizi作者: IRK 時(shí)間: 2025-3-29 19:52
Leveraging Motion Priors in Videos for Improving Human Segmentationlected segments have high precision and are directly used to finetune the model. In a newly collected surveillance camera dataset and a publicly available UrbanStreet dataset, our proposed method improves the performance of human segmentation across multiple scenes and modalities (i.e., RGB to Infra作者: 膽小懦夫 時(shí)間: 2025-3-30 01:28 作者: 淺灘 時(shí)間: 2025-3-30 04:25 作者: sigmoid-colon 時(shí)間: 2025-3-30 09:55 作者: 擔(dān)憂 時(shí)間: 2025-3-30 15:26
Donor Selection for Adults and Pediatricsut and show state-of-the-art results on the SURREAL and Unite the People datasets, outperforming recent approaches. Besides achieving state-of-the-art performance, our method also enables volumetric body-part segmentation.作者: 明確 時(shí)間: 2025-3-30 17:01
Franck Morschhauser,Pier Luigi Zinzani TPN with bi-directional training on pairs of frames. We apply the switchable TPN to three tasks: colorizing a gray-scale video based on a few colored key-frames, generating an HDR video from a low dynamic range (LDR) video and a few HDR frames, and propagating a segmentation mask from the first fra作者: FLEET 時(shí)間: 2025-3-30 20:52
https://doi.org/10.1007/978-1-84800-171-8proposed to predict the labels of unlabeled image sequences. With the newly estimated labeled sequences, the unified anchor embedding framework enables the feature learning process to be further facilitated. Extensive experimental results on the large-scale dataset show that the proposed method outp作者: eulogize 時(shí)間: 2025-3-31 03:15 作者: 環(huán)形 時(shí)間: 2025-3-31 05:49 作者: 誓言 時(shí)間: 2025-3-31 09:33
Acute and Chronic Pericarditis,ned to regress from any semantic parameter whose variation is observed in a training set, to the layer parameterization space. We show that this model not only allows to reproduce previous retargeting works, but generalizes the data generation capabilities to other semantic parameters such as clothi作者: 嫻熟 時(shí)間: 2025-3-31 15:56
Acute and Chronic Pericarditis,ne stage. So we further decompose the rain removal into multiple stages. Recurrent neural network is incorporated to preserve the useful information in previous stages and benefit the rain removal in later stages. We conduct extensive experiments on both synthetic and real-world datasets. Our propos作者: 殘廢的火焰 時(shí)間: 2025-3-31 21:01 作者: Cholagogue 時(shí)間: 2025-3-31 21:50
