作者: 率直 時間: 2025-3-21 23:04 作者: evasive 時間: 2025-3-22 01:08
Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead V in synthetic environments. However, model-free DRL models do not consider the dynamics in the real-world environments, and they often fail to generalize to new scenes. In this paper, we take a radical approach to bridge the gap between synthetic studies and real-world practices—We propose a novel, 作者: 喚起 時間: 2025-3-22 07:52
Improving Deep Visual Representation for Person Re-identification by Global and Local Image-languageverse auxiliary information has been utilized to improve the visual feature learning. In this paper, we propose to exploit natural language description as additional training supervisions for effective visual features. Compared with other auxiliary information, language can describe a specific perso作者: deadlock 時間: 2025-3-22 10:04
Learning 3D Shapes as Multi-layered Height-Maps Using 2D Convolutional NetworksLH) where at each grid location, we store multiple instances of height maps, thereby representing 3D shape detail that is hidden behind several layers of occlusion. We provide a novel view merging method for combining view dependent information (Eg. MLH descriptors) from multiple views. Because of t作者: neuron 時間: 2025-3-22 14:02
A Geometric Perspective on Structured Light CodingHamiltonian SL coding, a novel family of SL coding schemes that can recover 3D shape with high precision, with only a small number (as few as three) of images. We establish structural similarity between popular discrete (binary) SL coding methods, and Hamiltonian coding, which is a continuous coding作者: neuron 時間: 2025-3-22 20:14 作者: Ingenuity 時間: 2025-3-22 21:44 作者: 憤怒事實 時間: 2025-3-23 01:52
Super-Resolution and Sparse View CT Reconstructionedded in 3D volumes. To reconstruct such structures at resolutions below the Nyquist limit of the CT image sensor, we devise a new 3D structure tensor prior, which can be incorporated as a regularizer into more traditional proximal optimization methods for CT reconstruction. As a second, smaller con作者: Barter 時間: 2025-3-23 05:48 作者: 敵手 時間: 2025-3-23 12:21 作者: 寬宏大量 時間: 2025-3-23 16:13 作者: Keratin 時間: 2025-3-23 19:28
Image Generation from Sketch Constraint Using Contextual GANges due to the hard condition imposed by the translation process. Instead, we propose to use sketch as weak constraint, where the output edges do not necessarily follow the input edges. We address this problem using a novel . approach, where the sketch provides the image context for completing, or g作者: 共棲 時間: 2025-3-23 22:59 作者: 確保 時間: 2025-3-24 04:27 作者: 強(qiáng)行引入 時間: 2025-3-24 09:45
A Unified Framework for Multi-view Multi-class Object Pose Estimationound objects amidst complex background clutter. In this work, we present a scalable framework for accurately inferring six Degree-of-Freedom (6-DoF) pose for a large number of object classes from single or multiple views. To learn discriminative pose features, we integrate three new capabilities int作者: accrete 時間: 2025-3-24 13:14
Dynamic Task Prioritization for Multitask Learningortional to performance, and where difficulty changes over time. In contrast to curriculum learning, where easy tasks are prioritized above difficult tasks, we present several studies showing the importance of prioritizing difficult tasks first. We observe that imbalances in task difficulty can lead作者: Devastate 時間: 2025-3-24 17:48 作者: 強(qiáng)行引入 時間: 2025-3-24 19:33 作者: 偽書 時間: 2025-3-25 00:15 作者: restrain 時間: 2025-3-25 04:51 作者: 爭議的蘋果 時間: 2025-3-25 11:17 作者: forebear 時間: 2025-3-25 14:06 作者: 構(gòu)想 時間: 2025-3-25 17:49
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: macabre 時間: 2025-3-25 22:45 作者: amplitude 時間: 2025-3-26 03:56
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..978-3-030-01269-4978-3-030-01270-0Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: GNAW 時間: 2025-3-26 06:23
Silvana Lombardo,Massimiliano Petrihe ability of using 2D CNNs, our method is highly memory efficient in terms of input resolution compared to the voxel based input. Together with MLH descriptors and our multi view merging, we achieve the state-of-the-art result in classification on ModelNet dataset.作者: placebo-effect 時間: 2025-3-26 09:25 作者: microscopic 時間: 2025-3-26 13:29 作者: PET-scan 時間: 2025-3-26 17:22 作者: colloquial 時間: 2025-3-26 23:32
The internal structure of categories,nt instances. Multi-X outperforms significantly the state-of-the-art on publicly available datasets for diverse problems: multiple plane and rigid motion detection; motion segmentation; simultaneous plane and cylinder fitting; circle and line fitting.作者: 愛花花兒憤怒 時間: 2025-3-27 03:59 作者: 恭維 時間: 2025-3-27 09:05 作者: 絕食 時間: 2025-3-27 12:13
Look Before You Leap: Bridging Model-Free and Model-Based Reinforcement Learning for Planned-Ahead Veward. Experimental results suggest that our proposed method significantly outperforms the baselines and achieves the best on the real-world Room-to-Room dataset. Moreover, our scalable method is more generalizable when transferring to unseen environments.作者: 越自我 時間: 2025-3-27 16:20 作者: 自然環(huán)境 時間: 2025-3-27 20:05 作者: minimal 時間: 2025-3-28 00:26 作者: VOK 時間: 2025-3-28 06:10 作者: 尊重 時間: 2025-3-28 07:35
The Dynamics of China‘s Rejuvenationes the face by local homography transformations, which are estimated by a face rectification network. To encourage the image generation with canonical views, we apply a regularization based on the natural face distribution. We learn the rectification network and recognition network in an end-to-end 作者: GULP 時間: 2025-3-28 13:35 作者: Mercurial 時間: 2025-3-28 16:37
Brigitte Preissl,Laura Solimene in synthetic environments. However, model-free DRL models do not consider the dynamics in the real-world environments, and they often fail to generalize to new scenes. In this paper, we take a radical approach to bridge the gap between synthetic studies and real-world practices—We propose a novel, 作者: 深陷 時間: 2025-3-28 22:49
The Dynamics of Clusters and Innovationverse auxiliary information has been utilized to improve the visual feature learning. In this paper, we propose to exploit natural language description as additional training supervisions for effective visual features. Compared with other auxiliary information, language can describe a specific perso作者: 偶然 時間: 2025-3-28 23:37
Silvana Lombardo,Massimiliano PetriLH) where at each grid location, we store multiple instances of height maps, thereby representing 3D shape detail that is hidden behind several layers of occlusion. We provide a novel view merging method for combining view dependent information (Eg. MLH descriptors) from multiple views. Because of t作者: Colonoscopy 時間: 2025-3-29 06:55 作者: 膠狀 時間: 2025-3-29 07:42 作者: eucalyptus 時間: 2025-3-29 12:34 作者: Fillet,Filet 時間: 2025-3-29 15:56 作者: 半身雕像 時間: 2025-3-29 23:37 作者: figment 時間: 2025-3-30 00:57
Conceptual Organization and Its Development,over the 3D page shape by exploiting the intrinsic vector fields of the image. Based on the assumption that the curled page shape is a general cylindrical surface, we estimate the parameters related to the camera and the 3D shape model through weighted majority voting on the vector fields. Then the 作者: 突變 時間: 2025-3-30 07:43 作者: Atmosphere 時間: 2025-3-30 11:29 作者: 原諒 時間: 2025-3-30 14:50
The internal structure of categories,re of noisy observations originating from multiple instances of multiple classes. We extend the commonly used .-expansion-based technique with a new move in the label space. The move replaces a set of labels with the corresponding density mode in the model parameter domain, thus achieving fast and r作者: 招人嫉妒 時間: 2025-3-30 17:35 作者: 未開化 時間: 2025-3-30 22:44
The influence of contexts on typicalities,ound objects amidst complex background clutter. In this work, we present a scalable framework for accurately inferring six Degree-of-Freedom (6-DoF) pose for a large number of object classes from single or multiple views. To learn discriminative pose features, we integrate three new capabilities int作者: backdrop 時間: 2025-3-31 01:11
Conceptual Organization and Its Development,ortional to performance, and where difficulty changes over time. In contrast to curriculum learning, where easy tasks are prioritized above difficult tasks, we present several studies showing the importance of prioritizing difficult tasks first. We observe that imbalances in task difficulty can lead作者: 賞心悅目 時間: 2025-3-31 08:22
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234184.jpg作者: 變態(tài) 時間: 2025-3-31 10:38
https://doi.org/10.1007/978-3-030-01270-03D; artificial intelligence; image coding; image processing; image reconstruction; image segmentation; ima作者: FANG 時間: 2025-3-31 16:55
978-3-030-01269-4Springer Nature Switzerland AG 2018
