作者: Fortify 時間: 2025-3-21 21:14 作者: minion 時間: 2025-3-22 01:31
Cross-Spectral Image Patch Matching by Learning Features of the Spatially Connected Patches in a Shan. Extensive experiments shows that SCFDM outperforms the state-of-the-art methods on the cross-spectral dataset in terms of FPR95 and the training convergence. Meanwhile, it also demonstrates a better generalizability on a single spectral dataset.作者: Iniquitous 時間: 2025-3-22 08:02 作者: Visual-Field 時間: 2025-3-22 10:49
Robust Video Background Identification by Dominant Rigid Motion Estimationotions are also taken care of by checking their global consistency with the final estimated background motion. Lastly, by virtue of its efficiency, our method can deal with densely sampled trajectories. It outperforms several state-of-the-art motion segmentation methods on public datasets, both quan作者: 支架 時間: 2025-3-22 14:07
SMC: Single-Stage Multi-location Convolutional Network for Temporal Action Detectionation offsets to the default locations, as well as action categories. SMC in practice is faster than the existing methods (753 FPS on a Titan X Maxwell GPU) and achieves state-of-the-art performance on THUMOS’14 and MEXaction2.作者: 支架 時間: 2025-3-22 18:23 作者: innate 時間: 2025-3-22 21:52
Neural Abstract Style Transfer for Chinese Traditional Paintinginting. To promote research on this direction, we collect a new dataset with diverse photo-realistic images and Chinese traditional paintings (The dataset will be released at ..). In experiments, the proposed method shows more appealing stylized results in transferring the style of Chinese tradition作者: 乳白光 時間: 2025-3-23 04:32 作者: 步兵 時間: 2025-3-23 07:17 作者: occult 時間: 2025-3-23 12:37
The Dialectics of Liberation in Dark Timesition performance. Given this analysis, we train a network that far exceeds the state-of-the-art on the IJB-B face recognition dataset. This is currently one of the most challenging public benchmarks, and we surpass the state-of-the-art on both the identification and verification protocols.作者: 進取心 時間: 2025-3-23 14:33 作者: 傳授知識 時間: 2025-3-23 19:29
https://doi.org/10.1057/978-1-137-46236-7n. Extensive experiments shows that SCFDM outperforms the state-of-the-art methods on the cross-spectral dataset in terms of FPR95 and the training convergence. Meanwhile, it also demonstrates a better generalizability on a single spectral dataset.作者: 誘拐 時間: 2025-3-23 23:56
https://doi.org/10.1057/978-1-137-46236-7ning time and segmentation improvements comparable to state-of-the-art refinement approaches for semantic segmentation, as demonstrated by evaluations on multiple publicly available benchmark datasets.作者: ornithology 時間: 2025-3-24 04:47
Marcus Keller,Javier Irigoyen-Garcíaotions are also taken care of by checking their global consistency with the final estimated background motion. Lastly, by virtue of its efficiency, our method can deal with densely sampled trajectories. It outperforms several state-of-the-art motion segmentation methods on public datasets, both quan作者: critic 時間: 2025-3-24 10:08 作者: 甜食 時間: 2025-3-24 14:06 作者: STANT 時間: 2025-3-24 18:09 作者: Antagonism 時間: 2025-3-24 22:03 作者: 感激小女 時間: 2025-3-25 02:00
Yasemin Burcu Balo?lu,Sema Esen Soygeni?e original objective function of cGAN. We train our model on a large-scale dataset and present illustrative qualitative and quantitative analysis of our results. Our results vividly display the versatility and the proficiency of our methods through life-like colourization outcomes.作者: overreach 時間: 2025-3-25 04:17
Attributes Consistent Faces Generation Under Arbitrary Poses作者: 錢財 時間: 2025-3-25 09:12 作者: 勤勉 時間: 2025-3-25 14:36 作者: intoxicate 時間: 2025-3-25 16:13
Conference proceedings 2019bject detection and categorization, vision and language, video analysis and event recognition, face and gesture analysis, statistical methods and learning, performance evaluation, medical image analysis, document analysis, optimization methods, RGBD and depth camera processing, robotic vision, applications of computer vision.作者: Ligament 時間: 2025-3-25 23:32 作者: MIR 時間: 2025-3-26 02:24 作者: 巨大沒有 時間: 2025-3-26 08:09 作者: 主動脈 時間: 2025-3-26 11:36 作者: 罵人有污點 時間: 2025-3-26 16:17
https://doi.org/10.1007/978-3-030-71807-7lity of the co-occurrence of different objects in the training set. We validate the performance of our approach on standard single/multi-object datasets, showing state-of-the art performance in every dataset.作者: infringe 時間: 2025-3-26 17:22 作者: Saline 時間: 2025-3-26 21:52
Learning Image-to-Image Translation Using Paired and Unpaired Training Samplesvely improved results. Our model outperforms the baselines also in the case of purely paired and unpaired training data. To our knowledge, this is the first work to consider such hybrid setup in image-to-image translation.作者: fulmination 時間: 2025-3-27 04:54 作者: overweight 時間: 2025-3-27 06:57
Aligning Salient Objects to Queries: A Multi-modal and Multi-object Image Retrieval Frameworklity of the co-occurrence of different objects in the training set. We validate the performance of our approach on standard single/multi-object datasets, showing state-of-the art performance in every dataset.作者: PRISE 時間: 2025-3-27 12:48 作者: FACET 時間: 2025-3-27 14:53 作者: 可忽略 時間: 2025-3-27 20:49
Revolutionary Ecological Liberation: he single model trained on four holistic ReID datasets achieves competitive accuracy on these four datasets, as well as outperforms the state-of-the-art methods on two partial ReID datasets without training.作者: Emasculate 時間: 2025-3-27 23:11 作者: Endearing 時間: 2025-3-28 04:37 作者: Ringworm 時間: 2025-3-28 06:16 作者: Interregnum 時間: 2025-3-28 12:45
SCPNet: Spatial-Channel Parallelism Network for Joint Holistic and Partial Person Re-identificationen occluded by obstacles or other persons in practical scenarios, which makes partial person re-identification non-trivial. In this paper, we propose a spatial-channel parallelism network (SCPNet) in which each channel in the ReID feature pays attention to a given spatial part of the body. The spati作者: prolate 時間: 2025-3-28 18:13 作者: 眉毛 時間: 2025-3-28 19:58
Learning Image-to-Image Translation Using Paired and Unpaired Training Samplessufficient training data. Traditionally different approaches have been proposed depending on whether aligned image pairs or two sets of (unaligned) examples from both domains are available for training. While paired training samples might be difficult to obtain, the unpaired setup leads to a highly 作者: 600 時間: 2025-3-28 23:44 作者: 單片眼鏡 時間: 2025-3-29 04:30
Cross-Spectral Image Patch Matching by Learning Features of the Spatially Connected Patches in a Shams. We consider cross-spectral image patches can be matched because there exists a shared semantic feature space among them, in which the semantic features from different spectral images will be more independent of the spectral domains. To learn this shared feature space, we propose a progressive co作者: 殺死 時間: 2025-3-29 09:46
Semantic Segmentation Refinement by Monte Carlo Region Growing of High Confidence Detectionsonnected conditional random fields (CRFs) can significantly refine segmentation predictions. However, they rely on supervised parameter optimization that depends upon specific datasets and predictor modules. We propose an unsupervised method for semantic segmentation refinement that takes as input t作者: Osteons 時間: 2025-3-29 12:38
A Deep Blind Image Quality Assessment with Visual Importance Based Patch Scorelution is splitting the training image into patches, assigning each patch the quality score, while the assignment of patch score is not consistent with the human visual system (HVS) well. To address the problem, we propose a patch quality assignment strategy, introducing the weighting map to describ作者: 弄臟 時間: 2025-3-29 15:47 作者: senile-dementia 時間: 2025-3-29 19:48 作者: Hippocampus 時間: 2025-3-29 23:55
SAFE: Scale Aware Feature Encoder for Scene Text Recognitionoder (SAFE) that is designed specifically for encoding characters with different scales. SAFE is composed of a multi-scale convolutional encoder and a scale attention network. The multi-scale convolutional encoder targets at extracting character features under multiple scales, and the scale attentio作者: Aphorism 時間: 2025-3-30 07:17
Neural Abstract Style Transfer for Chinese Traditional Paintingtically appealing. Compared with western artistic painting, it is usually more visually abstract and textureless. Recently, neural network based style transfer methods have shown promising and appealing results which are mainly focused on western painting. It remains a challenging problem to preserv作者: savage 時間: 2025-3-30 11:32
Detector-in-Detector: Multi-level Analysis for Human-Partsral network (CNN). In this paper, we take the inherent correlation between the body and body parts into account and propose a new framework to boost up the detection performance of the multi-level objects. In particular, we adopt region-based object detection structure with two carefully designed de作者: 光滑 時間: 2025-3-30 16:18
Aligning Salient Objects to Queries: A Multi-modal and Multi-object Image Retrieval Frameworko jointly model sketches and text as input query modalities into a common embedding space, which is then further aligned with the image feature space. Our architecture also relies on a salient object detection through a supervised LSTM-based visual attention model learned from convolutional features作者: intellect 時間: 2025-3-30 20:27
Fast Light Field Disparity Estimation via a Parallel Filtered Cost Volume Approachss, such that costly optimizations that combine and refine depth maps are simplified. The algorithm involves shearing the light field over a range of disparities and computing a cost volume for each sheared sub-aperture image. A guided filter is then run on the computed cost for each disparity. For 作者: CUB 時間: 2025-3-30 23:18 作者: 赦免 時間: 2025-3-31 01:51 作者: 虛弱的神經 時間: 2025-3-31 07:06
Revolutionary Ecological Liberation: en occluded by obstacles or other persons in practical scenarios, which makes partial person re-identification non-trivial. In this paper, we propose a spatial-channel parallelism network (SCPNet) in which each channel in the ReID feature pays attention to a given spatial part of the body. The spati作者: 思鄉(xiāng)病 時間: 2025-3-31 12:55 作者: Expurgate 時間: 2025-3-31 13:31 作者: compel 時間: 2025-3-31 19:02 作者: HALO 時間: 2025-3-31 23:25
https://doi.org/10.1057/978-1-137-46236-7ms. We consider cross-spectral image patches can be matched because there exists a shared semantic feature space among them, in which the semantic features from different spectral images will be more independent of the spectral domains. To learn this shared feature space, we propose a progressive co作者: arbovirus 時間: 2025-4-1 02:17
https://doi.org/10.1057/978-1-137-46236-7onnected conditional random fields (CRFs) can significantly refine segmentation predictions. However, they rely on supervised parameter optimization that depends upon specific datasets and predictor modules. We propose an unsupervised method for semantic segmentation refinement that takes as input t作者: DAMN 時間: 2025-4-1 07:17
Marcus Keller,Javier Irigoyen-Garcíalution is splitting the training image into patches, assigning each patch the quality score, while the assignment of patch score is not consistent with the human visual system (HVS) well. To address the problem, we propose a patch quality assignment strategy, introducing the weighting map to describ
