派博傳思國際中心

標題: Titlebook: Computer Vision – ECCV 2020; 16th European Confer Andrea Vedaldi,Horst Bischof,Jan-Michael Frahm Conference proceedings 2020 Springer Natur [打印本頁]

作者: Confer    時間: 2025-3-21 19:28
書目名稱Computer Vision – ECCV 2020影響因子(影響力)




書目名稱Computer Vision – ECCV 2020影響因子(影響力)學(xué)科排名




書目名稱Computer Vision – ECCV 2020網(wǎng)絡(luò)公開度




書目名稱Computer Vision – ECCV 2020網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computer Vision – ECCV 2020被引頻次




書目名稱Computer Vision – ECCV 2020被引頻次學(xué)科排名




書目名稱Computer Vision – ECCV 2020年度引用




書目名稱Computer Vision – ECCV 2020年度引用學(xué)科排名




書目名稱Computer Vision – ECCV 2020讀者反饋




書目名稱Computer Vision – ECCV 2020讀者反饋學(xué)科排名





作者: cataract    時間: 2025-3-21 20:59

作者: avenge    時間: 2025-3-22 03:14
Marek Dabrowski,Jacek Rostowskid-background sub-task. Extensive experiments conducted with three popular datasets (i.e., Pascal VOC, Cityscapes and COCO) have demonstrated the effectiveness of our method in a wide range of noisy class labels scenarios. Code will be available at: ..
作者: instulate    時間: 2025-3-22 08:10
Uneven Growth in a Monetary Union,he effectiveness of our proposed motion representation method on downstream video understanding tasks, ...., action recognition task. Experimental results show that our method performs favorably against state-of-the-art methods.
作者: Pelago    時間: 2025-3-22 12:46

作者: Narrative    時間: 2025-3-22 16:06
Life, Hardship and Death at the Front,hard negative examples becomes feasible. This leads to more generalizable features, and image retrieval results that outperform state of the art for datasets with high intra-class variance. Code is available at: .
作者: Narrative    時間: 2025-3-22 19:57

作者: 誰在削木頭    時間: 2025-3-22 23:24
Paola Malanotte-Rizzoli,Valery N. Eremeevose loss functions that carefully integrate partial but correct annotations with complementary but noisy pseudo labels. Evaluation in the proposed novel setting requires full annotation on the test set. We collect the required annotations (Project page: . This work was part of Xiangyun Zhao’s intern
作者: conscience    時間: 2025-3-23 05:18

作者: 厚顏無恥    時間: 2025-3-23 06:39
Xing Xu,Helena Hing Wa Sit,Shen Chene: one synthesizes features of unseen classes/categories, while the other optimizes the embedding and performs the cross-modal alignment on the common embedding space. Specifically, two different types of generative adversarial networks learn collaboratively throughout the training process and the i
作者: GUMP    時間: 2025-3-23 10:14
Chinese Diplomacy in a Changing Worldxtensive experiments performed on THUMOS14 and ActivityNet datasets demonstrate that our proposed method is effective. Specifically, the average mAP of IoU thresholds from 0.1 to 0.9 on the THUMOS14 dataset is significantly improved from 27.9% to 30.0%.
作者: justify    時間: 2025-3-23 17:07

作者: drusen    時間: 2025-3-23 19:18
Chinese Diplomacy in a Changing World, an effective and simple fusion network is proposed for the late fusion stage. In our model, all networks are jointly trained in an end-to-end fashion. Extensive experiments demonstrate that our approach is effective and stable compared with other state-of-the-art methods (Code is available on: .).
作者: crumble    時間: 2025-3-24 00:15
SipMask: Spatial Information Preservation for Fast Image and Video Instance Segmentation,ge methods. Compared to the state-of-the-art single-stage TensorMask, SipMask obtains an absolute gain of 1.0% (mask AP), while providing a four-fold speedup. In terms of real-time capabilities, SipMask outperforms YOLACT with an absolute gain of 3.0% (mask AP) under similar settings, while operatin
作者: 緊張過度    時間: 2025-3-24 05:48
SemanticAdv: Generating Adversarial Examples via Attribute-Conditioned Image Editing,ability of . on both face recognition and general street-view images to show its generalization. We believe that our work can shed light on further understanding about vulnerabilities of DNNs as well as novel defense approaches. Our implementation is available at ..
作者: lactic    時間: 2025-3-24 06:41
Learning with Noisy Class Labels for Instance Segmentation,d-background sub-task. Extensive experiments conducted with three popular datasets (i.e., Pascal VOC, Cityscapes and COCO) have demonstrated the effectiveness of our method in a wide range of noisy class labels scenarios. Code will be available at: ..
作者: justify    時間: 2025-3-24 10:41
Self-supervised Motion Representation via Scattering Local Motion Cues,he effectiveness of our proposed motion representation method on downstream video understanding tasks, ...., action recognition task. Experimental results show that our method performs favorably against state-of-the-art methods.
作者: 按等級    時間: 2025-3-24 17:02

作者: molest    時間: 2025-3-24 22:45
Hard Negative Examples are Hard, but Useful,hard negative examples becomes feasible. This leads to more generalizable features, and image retrieval results that outperform state of the art for datasets with high intra-class variance. Code is available at: .
作者: Cervical-Spine    時間: 2025-3-24 23:16
ReActNet: Towards Precise Binary Neural Network with Generalized Activation Functions,unctions, to enable explicit learning of the distribution reshape and shift at near-zero extra cost. Lastly, we adopt a distributional loss to further enforce the binary network to learn similar output distributions as those of a real-valued network. We show that after incorporating all these ideas,
作者: glans-penis    時間: 2025-3-25 03:29
Object Detection with a Unified Label Space from Multiple Datasets,ose loss functions that carefully integrate partial but correct annotations with complementary but noisy pseudo labels. Evaluation in the proposed novel setting requires full annotation on the test set. We collect the required annotations (Project page: . This work was part of Xiangyun Zhao’s intern
作者: 迷住    時間: 2025-3-25 08:11
Lift, Splat, Shoot: Encoding Images from Arbitrary Camera Rigs by Implicitly Unprojecting to 3D,mentation, our model outperforms all baselines and prior work. In pursuit of the goal of learning dense representations for motion planning, we show that the representations inferred by our model enable interpretable end-to-end motion planning by “shooting” template trajectories into a bird’s-eye-vi
作者: visual-cortex    時間: 2025-3-25 12:17

作者: 用手捏    時間: 2025-3-25 18:40
Adversarial Background-Aware Loss for Weakly-Supervised Temporal Activity Localization,xtensive experiments performed on THUMOS14 and ActivityNet datasets demonstrate that our proposed method is effective. Specifically, the average mAP of IoU thresholds from 0.1 to 0.9 on the THUMOS14 dataset is significantly improved from 27.9% to 30.0%.
作者: Instrumental    時間: 2025-3-25 21:55

作者: Breach    時間: 2025-3-26 03:18

作者: Lymphocyte    時間: 2025-3-26 06:10
0302-9743 uter Vision, ECCV 2020, which was planned to be held in Glasgow, UK, during August 23-28, 2020. The conference was held virtually due to the COVID-19 pandemic..The 1360 revised papers presented in these proceedings were carefully reviewed and selected from a total of 5025 submissions. The papers dea
作者: 名詞    時間: 2025-3-26 10:06
Ond?ej Schneider,Pavel ?tepanekyle part. Last but not least, a prior distribution is imposed on the latent representation to ensure the elements of the category vector can be used as the probabilities over clusters. Comprehensive experiments demonstrate that the proposed approach outperforms state-of-the-art methods significantly on five public datasets (Project address: .).
作者: 裂縫    時間: 2025-3-26 16:42
The Officers: Backbone of the Army,dynamic blending filters. Finally, we combine the warped frames using the dynamic blending filters to generate intermediate frames. Experimental results show that the proposed algorithm outperforms the state-of-the-art video interpolation algorithms on several benchmark datasets. The source codes and pre-trained models are available at ..
作者: BOGUS    時間: 2025-3-26 18:44
The Eastern Question in 1870s Britaintensive experiments to demonstrate the benefits of our comprehensive captioning model. Our method establishes new state-of-the-art results in caption diversity, grounding, and controllability, and compares favourably to latest methods in caption quality. Our project website can be found at ..
作者: Allure    時間: 2025-3-26 23:06
Chinese Diplomacy in a Changing Worlds demonstrates that using a good learned embedding model can be more effective than sophisticated meta-learning algorithms. We believe that our findings motivate a rethinking of few-shot image classification benchmarks and the associated role of meta-learning algorithms. Code: ..
作者: ARCH    時間: 2025-3-27 04:15
Deep Image Clustering with Category-Style Representation,yle part. Last but not least, a prior distribution is imposed on the latent representation to ensure the elements of the category vector can be used as the probabilities over clusters. Comprehensive experiments demonstrate that the proposed approach outperforms state-of-the-art methods significantly on five public datasets (Project address: .).
作者: magnanimity    時間: 2025-3-27 07:44
BMBC: Bilateral Motion Estimation with Bilateral Cost Volume for Video Interpolation,dynamic blending filters. Finally, we combine the warped frames using the dynamic blending filters to generate intermediate frames. Experimental results show that the proposed algorithm outperforms the state-of-the-art video interpolation algorithms on several benchmark datasets. The source codes and pre-trained models are available at ..
作者: VEIL    時間: 2025-3-27 12:55

作者: 語言學(xué)    時間: 2025-3-27 16:13

作者: 出處    時間: 2025-3-27 21:22

作者: 里程碑    時間: 2025-3-28 00:26
0302-9743 processing; object detection; semantic segmentation; human pose estimation; 3d reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; object recognition; motion estimation..?..?.978-3-030-58567-9978-3-030-58568-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
作者: LURE    時間: 2025-3-28 04:17

作者: rheumatology    時間: 2025-3-28 10:05

作者: amplitude    時間: 2025-3-28 13:34

作者: 作嘔    時間: 2025-3-28 16:42

作者: Jargon    時間: 2025-3-28 21:18

作者: cognizant    時間: 2025-3-29 01:26

作者: 含糊其辭    時間: 2025-3-29 05:56

作者: 不可救藥    時間: 2025-3-29 08:41

作者: 擁護    時間: 2025-3-29 14:52
Deep Image Clustering with Category-Style Representation, propose a novel deep image clustering framework to learn a category-style latent representation in which the category information is disentangled from image style and can be directly used as the cluster assignment. To achieve this goal, mutual information maximization is applied to embed relevant i
作者: OUTRE    時間: 2025-3-29 17:42

作者: Ballad    時間: 2025-3-29 22:16
Improving Monocular Depth Estimation by Leveraging Structural Awareness and Complementary Datasets,tructural information exploitation, which leads to inaccurate spatial layout, discontinuous surface, and ambiguous boundaries. In this paper, we tackle this problem in three aspects. First, to exploit the spatial relationship of visual features, we propose a structure-aware neural network with spati
作者: reaching    時間: 2025-3-30 01:19
BMBC: Bilateral Motion Estimation with Bilateral Cost Volume for Video Interpolation,se a novel deep-learning-based video interpolation algorithm based on bilateral motion estimation. First, we develop the bilateral motion network with the bilateral cost volume to estimate bilateral motions accurately. Then, we approximate bi-directional motions to predict a different kind of bilate
作者: Restenosis    時間: 2025-3-30 08:05
Hard Negative Examples are Hard, but Useful,ser together in an embedding space than representations of images from different classes. Much work on triplet losses focuses on selecting the most useful triplets of images to consider, with strategies that select dissimilar examples from the same class or similar examples from different classes. T
作者: diathermy    時間: 2025-3-30 09:16

作者: 值得    時間: 2025-3-30 15:55

作者: 食道    時間: 2025-3-30 18:37
Object Detection with a Unified Label Space from Multiple Datasets,abel spaces. The practical benefits of such an object detector are obvious and significant—application-relevant categories can be picked and merged form arbitrary existing datasets. However, na?ve merging of datasets is not possible in this case, due to inconsistent object annotations. Consider an o
作者: Accord    時間: 2025-3-30 21:29

作者: 提名    時間: 2025-3-31 04:08

作者: blithe    時間: 2025-3-31 05:04

作者: 愛國者    時間: 2025-3-31 09:29

作者: fertilizer    時間: 2025-3-31 15:23

作者: 模范    時間: 2025-3-31 18:15
Adversarial Background-Aware Loss for Weakly-Supervised Temporal Activity Localization,eakly-supervised temporal activity localization struggle to recognize when an activity is not occurring. To address this issue, we propose a novel method named A2CL-PT. Two triplets of the feature space are considered in our approach: one triplet is used to learn discriminative features for each act
作者: gain631    時間: 2025-4-1 00:31

作者: Accomplish    時間: 2025-4-1 02:07

作者: congenial    時間: 2025-4-1 06:06

作者: 珠寶    時間: 2025-4-1 14:03

作者: 遭遇    時間: 2025-4-1 17:57

作者: nephritis    時間: 2025-4-1 18:38

作者: Definitive    時間: 2025-4-2 00:12
Uneven Growth in a Monetary Union,tical flow estimation to assist other tasks such as action recognition, frame prediction, video segmentation, etc. In this paper, we leverage the massive unlabeled video data to learn an accurate explicit motion representation that aligns well with the semantic distribution of the moving objects. Ou




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