作者: 嚴(yán)厲批評 時(shí)間: 2025-3-21 20:19
The Dynamics of Employee Relations-based paradigm, more traditional boundary-based methods such as Intelligent Scissor are still popular in practice as they allow users to have active control of the object boundaries. Existing methods for boundary-based segmentation solely rely on low-level image features, such as edges for boundary作者: 圣人 時(shí)間: 2025-3-22 04:17
https://doi.org/10.1007/978-1-349-14314-6photons scattered by the body as noise or disturbance to be disposed of, either by acquisition hardware (an anti-scatter grid) or by the reconstruction software. This increases the radiation dose delivered to the patient. Treating these scattered photons as a source of information, we solve an inver作者: 容易懂得 時(shí)間: 2025-3-22 06:19 作者: Aspiration 時(shí)間: 2025-3-22 12:05
Valeria Costantini,Massimiliano Mazzantil max/average pooling layer between the convolution and fully-connected layers to retain translation invariance and shape preserving (aware of shape difference) properties based on the shift theorem of the Fourier transform. Thanks to the ability to handle image misalignment while keeping important 作者: 綁架 時(shí)間: 2025-3-22 13:41
https://doi.org/10.1007/978-94-007-5089-0, speed, also depends on the other factors such as memory access cost and platform characterics. Thus, this work proposes to evaluate the direct metric on the target platform, beyond only considering FLOPs. Based on a series of controlled experiments, this work derives several practical . for effici作者: 綁架 時(shí)間: 2025-3-22 17:51
Carbon Leakage and Trade Adjustment Policiesadapt it to the end-to-end training of visual features on large-scale datasets. In this work, we present DeepCluster, a clustering method that jointly learns the parameters of a neural network and the cluster assignments of the resulting features. DeepCluster iteratively groups the features with a s作者: 到婚嫁年齡 時(shí)間: 2025-3-22 22:51 作者: 縮短 時(shí)間: 2025-3-23 05:19 作者: 有機(jī)體 時(shí)間: 2025-3-23 09:19
https://doi.org/10.1007/978-94-015-0945-9understandings. Data-driven approaches, such as deep neural networks, can deal with the ambiguity inherent in this task to some extent, but it is extremely expensive to acquire the temporal annotations of a large-scale video dataset. To leverage the plentiful web-crawled videos to improve the perfor作者: 殘忍 時(shí)間: 2025-3-23 10:50 作者: 異端邪說2 時(shí)間: 2025-3-23 17:34
https://doi.org/10.1057/9780230625433ing-time illusion. Producing such visual effects, however, typically requires using a large number of cameras/images surrounding the subject. In this paper, we present a learning-based solution that is capable of producing the bullet-time effect from only a small set of images. Specifically, we pres作者: 無意 時(shí)間: 2025-3-23 19:45 作者: Vertical 時(shí)間: 2025-3-23 22:38 作者: 不安 時(shí)間: 2025-3-24 03:39
https://doi.org/10.1057/9780230625433t single-shot model. The proposed PersonLab model tackles both semantic-level reasoning and object-part associations using part-based modeling. Our model employs a convolutional network which learns to detect individual keypoints and predict their relative displacements, allowing us to group keypoin作者: biosphere 時(shí)間: 2025-3-24 06:39 作者: Bombast 時(shí)間: 2025-3-24 14:21
https://doi.org/10.1007/978-3-030-01264-93D; artificial intelligence; computer vision; image coding; image processing; image reconstruction; image 作者: 眨眼 時(shí)間: 2025-3-24 16:04 作者: convert 時(shí)間: 2025-3-24 21:12 作者: Antagonism 時(shí)間: 2025-3-25 02:57
Computer Vision – ECCV 2018978-3-030-01264-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 傳授知識 時(shí)間: 2025-3-25 03:36
Conference proceedings 2018, ECCV 2018, held in Munich, Germany, in September 2018..The 776 revised papers presented were carefully reviewed and selected from 2439 submissions. The papers are organized in topical?sections on learning for vision; computational photography; human analysis; human sensing; stereo and reconstructi作者: aquatic 時(shí)間: 2025-3-25 10:39
The dynamics of industrial Conflict to previous methods in handling text instances of irregular shapes, for example, curved text. Experiments on ICDAR2013, ICDAR2015 and Total-Text demonstrate that the proposed method achieves state-of-the-art results in both scene text detection and end-to-end text recognition tasks.作者: Mortar 時(shí)間: 2025-3-25 13:52 作者: 薄膜 時(shí)間: 2025-3-25 15:54 作者: 除草劑 時(shí)間: 2025-3-25 20:58 作者: INCUR 時(shí)間: 2025-3-26 04:13
Michael A. Pagano,Robert Leonardito compose classifiers for verb-noun pairs. We also provide benchmarks on several dataset for zero-shot learning including both image and video. We hope our method, dataset and baselines will facilitate future research in this direction.作者: Optimum 時(shí)間: 2025-3-26 06:25
Mask TextSpotter: An End-to-End Trainable Neural Network for Spotting Text with Arbitrary Shapes to previous methods in handling text instances of irregular shapes, for example, curved text. Experiments on ICDAR2013, ICDAR2015 and Total-Text demonstrate that the proposed method achieves state-of-the-art results in both scene text detection and end-to-end text recognition tasks.作者: subordinate 時(shí)間: 2025-3-26 12:30 作者: foppish 時(shí)間: 2025-3-26 15:50
Graph Distillation for Action Detection with Privileged Modalitiese scarce. We evaluate our approach on action classification and detection tasks in multimodal videos, and show that our model outperforms the state-of-the-art by a large margin on the NTU RGB+D and PKU-MMD benchmarks. The code is released at ..作者: 賠償 時(shí)間: 2025-3-26 19:35
Learning to Dodge A Bullet: Concyclic View Morphing via Deep Learning motion field and per-pixel visibility for new view interpolation. Comprehensive experiments on synthetic and real data show that our new framework outperforms the state-of-the-art and provides an inexpensive and practical solution for producing the bullet-time effects.作者: 的闡明 時(shí)間: 2025-3-26 21:58
Compositional Learning for Human Object Interactionto compose classifiers for verb-noun pairs. We also provide benchmarks on several dataset for zero-shot learning including both image and video. We hope our method, dataset and baselines will facilitate future research in this direction.作者: 輕快走過 時(shí)間: 2025-3-27 02:31 作者: linguistics 時(shí)間: 2025-3-27 06:51
https://doi.org/10.1007/978-94-007-5089-0c on the target platform, beyond only considering FLOPs. Based on a series of controlled experiments, this work derives several practical . for efficient network design. Accordingly, a new architecture is presented, called .. Comprehensive ablation experiments verify that our model is the state-of-the-art in terms of speed and accuracy tradeoff.作者: cogent 時(shí)間: 2025-3-27 12:13
Social Forces, Space and Boundariess of data are added and trained on. (iii) A novel loss function, which takes into account both the geometry of the problem and the new types of data, is propose. Our network allows a substantial boost in performance: from 36.1% gained by SOTA algorithms to 45.9%.作者: 共同給與 時(shí)間: 2025-3-27 16:25 作者: 處理 時(shí)間: 2025-3-27 20:19 作者: Aspirin 時(shí)間: 2025-3-27 22:08
https://doi.org/10.1007/978-1-349-14314-6 make the solution numerically efficient. The resulting tomographic reconstruction is more accurate than traditional CT, while enabling significant dose reduction and chemical decomposition. Demonstrations include both simulations based on a standard medical phantom and a real scattering tomography experiment.作者: 方舟 時(shí)間: 2025-3-28 03:00 作者: 過分自信 時(shí)間: 2025-3-28 09:59
X-Ray Computed Tomography Through Scatter make the solution numerically efficient. The resulting tomographic reconstruction is more accurate than traditional CT, while enabling significant dose reduction and chemical decomposition. Demonstrations include both simulations based on a standard medical phantom and a real scattering tomography experiment.作者: cutlery 時(shí)間: 2025-3-28 10:42 作者: 離開可分裂 時(shí)間: 2025-3-28 16:51 作者: Frequency-Range 時(shí)間: 2025-3-28 19:46 作者: 袋鼠 時(shí)間: 2025-3-29 01:14
Shift-Net: Image Inpainting via Deep Feature Rearrangementature 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 作者: 并置 時(shí)間: 2025-3-29 03:42 作者: 虛弱的神經(jīng) 時(shí)間: 2025-3-29 09:31
Modular Generative Adversarial Networksains, and then combined to construct specific GAN networks at test time, according to the specific image translation task. This leads to ModularGAN’s superior flexibility of generating (or translating to) an image in any desired domain. Experimental results demonstrate that our model not only presen作者: outrage 時(shí)間: 2025-3-29 12:03 作者: Dendritic-Cells 時(shí)間: 2025-3-29 15:37
Single Image Intrinsic Decomposition Without a Single Intrinsic Imageam module that performs intrinsic decomposition on a single input image. We demonstrate the effectiveness of our framework through extensive experimental study on both synthetic and real-world datasets, showing superior performance over previous approaches in both single-image and multi-image settin作者: 微粒 時(shí)間: 2025-3-29 22:40
PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric stem achieves COCO test-dev keypoint average precision of 0.665 using single-scale inference and 0.687 using multi-scale inference, significantly outperforming all previous bottom-up pose estimation systems. We are also the first bottom-up method to report competitive results for the person class in作者: 越自我 時(shí)間: 2025-3-30 01:00 作者: Neutropenia 時(shí)間: 2025-3-30 04:29
The dynamic context of employee relationsature 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 作者: Tincture 時(shí)間: 2025-3-30 12:03
The Dynamics of Employee Relationsr interactions (e.g. clicks on boundary points) as input and predicts semantically meaningful boundaries that match user intentions. Our method explicitly models the dependency of boundary extraction results on image content and user interactions. Experiments on two public interactive segmentation b作者: Insensate 時(shí)間: 2025-3-30 14:13
https://doi.org/10.1007/978-94-010-1024-5ains, and then combined to construct specific GAN networks at test time, according to the specific image translation task. This leads to ModularGAN’s superior flexibility of generating (or translating to) an image in any desired domain. Experimental results demonstrate that our model not only presen作者: vanquish 時(shí)間: 2025-3-30 20:12
https://doi.org/10.1007/978-94-015-0945-9n the generated summaries and web videos is presented, and the overall framework is further formulated into a unified conditional variational encoder-decoder, called variational encoder-summarizer-decoder (VESD). Experiments conducted on the challenging datasets CoSum and TVSum demonstrate the super作者: 陪審團(tuán)每個(gè)人 時(shí)間: 2025-3-31 00:31 作者: Phenothiazines 時(shí)間: 2025-3-31 02:53 作者: 草率男 時(shí)間: 2025-3-31 08:13
https://doi.org/10.1057/9780230625433llows us to efficiently learn our model from a small-scale task-driven saliency dataset with sparse labels (captured under a single task condition). Experimental results show that our method outperforms the baselines and prior works, achieving state-of-the-art performance on a newly collected benchm作者: enumaerate 時(shí)間: 2025-3-31 12:26 作者: Genome 時(shí)間: 2025-3-31 14:41 作者: 費(fèi)解 時(shí)間: 2025-3-31 21:27 作者: 獨(dú)裁政府 時(shí)間: 2025-3-31 22:28 作者: 是突襲 時(shí)間: 2025-4-1 05:22 作者: 感激小女 時(shí)間: 2025-4-1 08:53 作者: gout109 時(shí)間: 2025-4-1 13:02
