作者: 否決 時間: 2025-3-21 20:41 作者: 少量 時間: 2025-3-22 03:00 作者: 和平主義者 時間: 2025-3-22 07:31 作者: expdient 時間: 2025-3-22 09:58 作者: notification 時間: 2025-3-22 13:53
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filtersar underlying structures such as 3D point clouds. Towards this we propose a novel convolutional architecture, termed SpiderCNN, to efficiently extract geometric features from point clouds. SpiderCNN is comprised of units called SpiderConv, which extend convolutional operations from regular grids to 作者: notification 時間: 2025-3-22 18:54 作者: 打谷工具 時間: 2025-3-22 23:07
Interpretable Basis Decomposition for Visual Explanations of the system. Current neural networks used for visual recognition are generally used as black boxes that do not provide any human interpretable justification for a prediction. In this work we propose a new framework called Interpretable Basis Decomposition for providing visual explanations for cl作者: glowing 時間: 2025-3-23 05:13
Partial Adversarial Domain Adaptationarial networks generally assume identical label space across different domains. In the presence of big data, there is strong motivation of transferring deep models from existing big domains to unknown small domains. This paper introduces partial domain adaptation as a new domain adaptation scenario,作者: engender 時間: 2025-3-23 08:04 作者: 變化無常 時間: 2025-3-23 12:13
Toward Scale-Invariance and Position-Sensitive Region Proposal Networksaccuracy of an object detection method has been shown highly related to the average recall (AR) of the proposals. In this work, we propose an advanced object proposal network in favour of translation-invariance for objectness classification, translation-variance for bounding box regression, large ef作者: Additive 時間: 2025-3-23 16:09 作者: 真實的人 時間: 2025-3-23 18:50 作者: visual-cortex 時間: 2025-3-23 23:48 作者: 美麗的寫 時間: 2025-3-24 04:52 作者: 高原 時間: 2025-3-24 10:23 作者: 多樣 時間: 2025-3-24 12:53 作者: 即席 時間: 2025-3-24 18:43 作者: neoplasm 時間: 2025-3-24 21:41 作者: attenuate 時間: 2025-3-25 00:05 作者: 抗生素 時間: 2025-3-25 06:49 作者: 姑姑在炫耀 時間: 2025-3-25 10:27 作者: Influx 時間: 2025-3-25 14:49 作者: GREG 時間: 2025-3-25 18:31 作者: delta-waves 時間: 2025-3-25 22:17 作者: Halfhearted 時間: 2025-3-26 01:39
https://doi.org/10.1007/978-3-030-70019-5 to assess the caption quality. The experiments we performed to assess the proposed metric, show improvements upon the state of the art in terms of correlation with human judgements and demonstrate its superior robustness to distractions.作者: acclimate 時間: 2025-3-26 05:59
An Infrared Point Source Survey,hical architecture from classical CNNs, which allows it to extract semantic deep features. Experiments on ModelNet40 demonstrate that SpiderCNN achieves state-of-the-art accuracy . on standard benchmarks, and shows competitive performance on segmentation task.作者: 流動性 時間: 2025-3-26 10:02
,Dresden at the Time of Heinrich Schütz,ject proposal network significantly improves the AR at 1,000 proposals by . and . on PASCAL VOC and COCO dataset respectively and has a fast inference time of 44.8 ms for input image size of .. Empirical studies have also shown that the proposed method is class-agnostic to be generalised for general object proposal.作者: 使絕緣 時間: 2025-3-26 15:06
The Early Career Researcher‘s Toolboxers so that they are optimal for adapting to the target FGVC task. Based on MetaFGNet, we also propose a simple yet effective scheme for selecting more useful samples from the auxiliary data. Experiments on benchmark FGVC datasets show the efficacy of our proposed method.作者: 碎片 時間: 2025-3-26 17:18
NNEval: Neural Network Based Evaluation Metric for Image Captioning to assess the caption quality. The experiments we performed to assess the proposed metric, show improvements upon the state of the art in terms of correlation with human judgements and demonstrate its superior robustness to distractions.作者: 破布 時間: 2025-3-26 23:18
SpiderCNN: Deep Learning on Point Sets with Parameterized Convolutional Filtershical architecture from classical CNNs, which allows it to extract semantic deep features. Experiments on ModelNet40 demonstrate that SpiderCNN achieves state-of-the-art accuracy . on standard benchmarks, and shows competitive performance on segmentation task.作者: 歡騰 時間: 2025-3-27 03:39 作者: 暴露他抗議 時間: 2025-3-27 06:17
Fine-Grained Visual Categorization Using Meta-learning Optimization with Sample Selection of Auxiliaers so that they are optimal for adapting to the target FGVC task. Based on MetaFGNet, we also propose a simple yet effective scheme for selecting more useful samples from the auxiliary data. Experiments on benchmark FGVC datasets show the efficacy of our proposed method.作者: Needlework 時間: 2025-3-27 10:41 作者: 有毒 時間: 2025-3-27 15:47 作者: 轉(zhuǎn)向 時間: 2025-3-27 18:23
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..978-3-030-01236-6978-3-030-01237-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Outspoken 時間: 2025-3-28 01:28
Computer Vision – ECCV 2018978-3-030-01237-3Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 千篇一律 時間: 2025-3-28 05:10 作者: 厭惡 時間: 2025-3-28 08:03
Movement of Persons under Schengen,orld noisy images is much more complex than AWGN, and is hard to be modeled by simple analytical distributions. As a result, many state-of-the-art denoising methods in literature become much less effective when applied to real-world noisy images captured by CCD or CMOS cameras. In this paper, we dev作者: CLASH 時間: 2025-3-28 13:39
https://doi.org/10.1007/978-3-030-70019-5ning systems. Existing metrics to automatically evaluate image captioning systems fail to achieve a satisfactory level of correlation with human judgements at the sentence level. Moreover, these metrics, unlike humans, tend to focus on specific aspects of quality, such as the n-gram overlap or the s作者: Sinus-Node 時間: 2025-3-28 18:08 作者: 可轉(zhuǎn)變 時間: 2025-3-28 20:56 作者: Iatrogenic 時間: 2025-3-29 01:45
An Infrared Point Source Survey,ar underlying structures such as 3D point clouds. Towards this we propose a novel convolutional architecture, termed SpiderCNN, to efficiently extract geometric features from point clouds. SpiderCNN is comprised of units called SpiderConv, which extend convolutional operations from regular grids to 作者: Communal 時間: 2025-3-29 04:46 作者: 遺產(chǎn) 時間: 2025-3-29 08:25
,The “Dragon” Nebula G28.34+0.06,s of the system. Current neural networks used for visual recognition are generally used as black boxes that do not provide any human interpretable justification for a prediction. In this work we propose a new framework called Interpretable Basis Decomposition for providing visual explanations for cl作者: Irremediable 時間: 2025-3-29 14:04
https://doi.org/10.1007/978-3-662-44969-1arial networks generally assume identical label space across different domains. In the presence of big data, there is strong motivation of transferring deep models from existing big domains to unknown small domains. This paper introduces partial domain adaptation as a new domain adaptation scenario,作者: 自負的人 時間: 2025-3-29 19:26
,The “Snake” Nebula G11.11–0.12,y of modeling diversity. If videos are lengthy like hours-long egocentric videos, it is necessary to track the temporal structures of the videos and enforce local diversity. The local diversity refers to that the shots selected from a short time duration are diverse but visually similar shots are al作者: ornithology 時間: 2025-3-29 21:16 作者: 純樸 時間: 2025-3-30 01:35 作者: 廣大 時間: 2025-3-30 04:45 作者: Abominate 時間: 2025-3-30 10:50
The Early Career Researcher‘s Toolbox a pre-trained model, we extract representative 2D kernel centroids using k-means clustering. Each centroid replaces the corresponding kernels of the same cluster, and we use indexed representations instead of saving whole kernels. Kernels in the same cluster share their weights, and we fine-tune th作者: Glaci冰 時間: 2025-3-30 12:38
The Early Career Researcher‘s Toolboxmples. To employ large models for FGVC without suffering from overfitting, existing methods usually adopt a strategy of pre-training the models using a rich set of auxiliary data, followed by fine-tuning on the target FGVC task. However, the objective of pre-training does not take the target task in作者: 成份 時間: 2025-3-30 17:19
The Early Career Researcher‘s Toolboxtion and recognition tasks. This paper presents a novel image synthesis technique that aims to generate a large amount of annotated scene text images for training accurate and robust scene text detection and recognition models. The proposed technique consists of three innovative designs. First, it r作者: Buttress 時間: 2025-3-30 23:41
Richard Oastler on the Origins of Chartismion. Due to limited representation ability, it is challenging to train very tiny networks for complicated tasks like detection. To the best of our knowledge, our method, called Quantization Mimic, is the first one focusing on very tiny networks. We utilize two types of acceleration methods: mimic an作者: Water-Brash 時間: 2025-3-31 04:10
Richard Oastler on the Origins of Chartism The underlying assumptions made by solvers are often not satisfied and many problems are inherently ill-posed. In this paper, we propose a neural nonlinear least squares optimization algorithm which learns to effectively optimize these cost functions even in the presence of adversities. Unlike trad作者: 生存環(huán)境 時間: 2025-3-31 07:35 作者: 向下 時間: 2025-3-31 10:36 作者: predict 時間: 2025-3-31 14:07
978-3-030-01236-6Springer Nature Switzerland AG 2018作者: AFFIX 時間: 2025-3-31 20:10
Learning 3D Keypoint Descriptors for Non-rigid Shape Matchingr for it. Experimental results for non-rigid shape matching on several benchmarks demonstrate the superior performance of our learned descriptors over traditional descriptors and the state-of-the-art learning-based alternatives.作者: 捏造 時間: 2025-4-1 00:07
A Trilateral Weighted Sparse Coding Scheme for Real-World Image Denoisinghe solution and convergence of the proposed algorithm are analyzed. Extensive experiments demonstrate that the proposed TWSC scheme outperforms state-of-the-art denoising methods on removing realistic noise.作者: 啜泣 時間: 2025-4-1 03:10
VideoMatch: Matching Based Video Object Segmentationf the proposed method on the challenging DAVIS-16, DAVIS-17, Youtube-Objects and JumpCut datasets. Extensive results show that our method achieves comparable performance without fine-tuning and is much more favorable in terms of computational time.
