標(biāo)題: Titlebook: Image and Graphics; 11th International C Yuxin Peng,Shi-Min Hu,Kun Xu Conference proceedings 2021 Springer Nature Switzerland AG 2021 artif [打印本頁] 作者: FAD 時(shí)間: 2025-3-21 16:38
書目名稱Image and Graphics影響因子(影響力)
書目名稱Image and Graphics影響因子(影響力)學(xué)科排名
書目名稱Image and Graphics網(wǎng)絡(luò)公開度
書目名稱Image and Graphics網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Image and Graphics被引頻次
書目名稱Image and Graphics被引頻次學(xué)科排名
書目名稱Image and Graphics年度引用
書目名稱Image and Graphics年度引用學(xué)科排名
書目名稱Image and Graphics讀者反饋
書目名稱Image and Graphics讀者反饋學(xué)科排名
作者: Immortal 時(shí)間: 2025-3-21 20:27 作者: Plaque 時(shí)間: 2025-3-22 01:33 作者: reception 時(shí)間: 2025-3-22 04:41
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/i/image/461487.jpg作者: Crumple 時(shí)間: 2025-3-22 12:42 作者: Antecedent 時(shí)間: 2025-3-22 16:00
Learning Cross-Domain Descriptors for 2D-3D Matching with Hard Triplet Loss and Spatial Transformer and provides support for multi-sensor fusion. Specifically, the cross-domain descriptor extraction between 2D images and 3D point clouds is a solution to achieve 2D-3D matching. Essentially, the 3D point cloud volumes and 2D image patches can be sampled based on the keypoints of 3D point clouds and作者: Myofibrils 時(shí)間: 2025-3-22 19:00
A Stereo Matching Method for Three-Dimensional Eye Localization of Autostereoscopic Display eye localization. Due to the need of displaying high frame rate video images, higher requirements are put forward on the real-time performance of the three-dimensional eye localization algorithm. The three-dimensional measurement of the distance of the eye is particularly complicated, and stereo ma作者: 表示向下 時(shí)間: 2025-3-22 23:31 作者: 滲透 時(shí)間: 2025-3-23 03:57 作者: Homocystinuria 時(shí)間: 2025-3-23 06:59
Bird Keypoint Detection via Exploiting 2D Texture and 3D Geometric Featureson methods have poor performance on symmetric keypoints, because they mainly use texture features only, which usually can not distinguish between symmetric keypoints, such as the keypoints on left and right legs. Besides, these methods cannot deal well with the complex image background. Therefore, w作者: 一個(gè)攪動(dòng)不安 時(shí)間: 2025-3-23 11:24 作者: palette 時(shí)間: 2025-3-23 15:50
Improved 3D Morphable Model for Facial Action Unit Synthesis face model that combines facial action coding system (FACS) and 3D morphable model (3DMM). Our proposed 3D face model can be used for 3D facial expression synthesis with local action units (AUs). To be specific, AUs are introduced as prior knowledge into the 3D face model to capture the anatomicall作者: 媒介 時(shí)間: 2025-3-23 20:54 作者: acrophobia 時(shí)間: 2025-3-24 01:57
KeypointNet: Ranking Point Cloud for Convolution Neural Networkowever, the irregularity and disorder of point clouds make the convolution operation ill-suited to preserve the spatial-local structure and make the existing convolution networks very shallow. In order to solve the problems, we propose a novel pre-processor network named KeypointNet which ranks the 作者: BROW 時(shí)間: 2025-3-24 04:27
Geometric Context Sensitive Loss and Its Application for Nonrigid Structure from?Motionevious techniques utilize Mean Square Error (MSE) loss function to measure the difference between the prediction coordinates and its corresponding ground-truth in training step, which usually assumes that coordinates are independent to each other without considering their correlations, neglecting th作者: 狂熱文化 時(shí)間: 2025-3-24 08:49 作者: 用肘 時(shí)間: 2025-3-24 13:35 作者: 可能性 時(shí)間: 2025-3-24 18:18
No-Reference Image Quality Assessment via Broad Learning Systemimage processing. Even though, a large number of super parameters make the computational complexity gradually increase. Surprisingly, Broad Learning System (BLS) can transform the deep structure of DL into a flat and visual network structure, which reduces the difficulty for practical applications. 作者: 蜈蚣 時(shí)間: 2025-3-24 19:40
Hindsight Curriculum Generation Based Multi-Goal Experience Replaypseudo goals—has shown the potential to learn from failed experiences. However, not all the pseudo goals are well-explored to provide reliable value estimates. In view of value estimation, the agent should learn from achievable goals towards desired goals distribution progressively. To tackle the pr作者: 責(zé)任 時(shí)間: 2025-3-25 02:11
Gesture-Based Autonomous Diving Buddy for Underwater Photographyresents an Autonomous Diving Buddy to assist divers and ensure their safety. In this paper, considering the limitations of the previous underwater interaction, we proposed an algorithm based on gesture recognition, assisted by underwater image enhancement and target tracking, which can effectively c作者: 表主動(dòng) 時(shí)間: 2025-3-25 04:22 作者: BATE 時(shí)間: 2025-3-25 09:49 作者: Cumbersome 時(shí)間: 2025-3-25 13:48
hallenging part in the translation of historical classics. However, it is tough to recognize the terms directly from ancient Chinese due to the flexible syntactic of ancient Chinese and the word segmentation errors of ancient Chinese will lead to more errors in term translation extraction. Consideri作者: 有特色 時(shí)間: 2025-3-25 16:37
Jinhao Yu,Guoliang Yan,Xiuqi Xu,Jian Wang,Shuhan Chen,Xuelong Huhallenging part in the translation of historical classics. However, it is tough to recognize the terms directly from ancient Chinese due to the flexible syntactic of ancient Chinese and the word segmentation errors of ancient Chinese will lead to more errors in term translation extraction. Consideri作者: ventilate 時(shí)間: 2025-3-25 23:22 作者: STAT 時(shí)間: 2025-3-26 00:40 作者: 松雞 時(shí)間: 2025-3-26 08:06 作者: 使服水土 時(shí)間: 2025-3-26 11:21 作者: 比喻好 時(shí)間: 2025-3-26 15:25 作者: entrance 時(shí)間: 2025-3-26 19:35 作者: 脫落 時(shí)間: 2025-3-26 22:46
Jing Yue,Guojun liu,Lizhuan Huangse algorithm, and the scalability of this algorithm is greatly restricted by its inherently sequential nature where only one hidden layer can be trained at one time. In order to speed up the training of deep networks, this paper mainly focuses on pre-training phase and proposes a pipelined pre-train作者: 比賽用背帶 時(shí)間: 2025-3-27 04:41
Xiaoyun Fengse algorithm, and the scalability of this algorithm is greatly restricted by its inherently sequential nature where only one hidden layer can be trained at one time. In order to speed up the training of deep networks, this paper mainly focuses on pre-training phase and proposes a pipelined pre-train作者: bourgeois 時(shí)間: 2025-3-27 05:46
Hao Zhang,Fei Yuan,Jiajun Chen,Xinyu He,Yi Zhuis semantic classification of a text unit as positive or negative using lexical and/or contextual clues in a natural language system. From the input side, it is observed that social media as a sub-language often uses emoticons mixed with text to show emotions. Most emoticons, e.g. :=), are not natur作者: Lipoprotein(A) 時(shí)間: 2025-3-27 10:40
Xiaojie Wang,Fei Li,Shujie Zhou,Hong Dure-level opinion mining are dedicated to extract explicitly appeared features and opinion words. However, among the numerous kinds of reviews on the web, there are a significant number of reviews that contain only opinion words which imply some product features. The identification of such implicit f作者: agglomerate 時(shí)間: 2025-3-27 14:57 作者: Acupressure 時(shí)間: 2025-3-27 19:04 作者: 不容置疑 時(shí)間: 2025-3-28 00:12 作者: 拍翅 時(shí)間: 2025-3-28 04:56 作者: 同謀 時(shí)間: 2025-3-28 09:53 作者: 噴出 時(shí)間: 2025-3-28 12:20
3D Reconstruction from Single-View Image Using Feature Selectionraining and Inference are slightly different in this module. Using this module, we achieve better performance with about 18% parameters addition and comparable performance with about 30% model’s parameters decrease based on the Pix2Vox [.] framework.作者: 表被動(dòng) 時(shí)間: 2025-3-28 15:47 作者: 全國性 時(shí)間: 2025-3-28 20:54 作者: affinity 時(shí)間: 2025-3-28 23:19 作者: 吃掉 時(shí)間: 2025-3-29 05:36
Gesture-Based Autonomous Diving Buddy for Underwater Photographyomplete the task of underwater gesture recognition. Then we experimented on the algorithm and the system. Experiments show that the algorithm performs well and the proposed ADB can make corresponding actions correctly according to gestures.作者: 壁畫 時(shí)間: 2025-3-29 08:09 作者: MUMP 時(shí)間: 2025-3-29 12:12 作者: abduction 時(shí)間: 2025-3-29 19:06
Learning Cross-Domain Descriptors for 2D-3D Matching with Hard Triplet Loss and Spatial Transformer e HAS-Net introduces the spatial transformer network (STN) to overcome the translation, scale, rotation and more generic warping of 2D image patches. In addition, the HAS-Net uses the negative sample sampling strategy of hard triplet loss to solve the uncertainty of randomly sampling negative sample作者: 發(fā)誓放棄 時(shí)間: 2025-3-29 20:11 作者: insightful 時(shí)間: 2025-3-30 03:36
Scaling Invariant Harmonic Wave Kernel Signature for 3D Point Cloud SimilarityS is a shape descriptor involving in the Laplace-Beltrami operator, which can effectively extract geometric and topological information from 3D point cloud models. Based on SIHWKS, the modified Hausdorff distance between SIHWKS values of 3D point cloud model is calculated as similarity measurement, 作者: receptors 時(shí)間: 2025-3-30 05:13
PST-NET: Point Cloud Sampling via Point-Based Transformerh remarkable improvement for shape classification. Also various combinations of relation functions for self-attention are analyzed based on controlled experiments. The result shows that concatenation is more suitable for self-attention in sampling.作者: 慢慢沖刷 時(shí)間: 2025-3-30 09:56
Bird Keypoint Detection via Exploiting 2D Texture and 3D Geometric Featurese fused to obtain the final keypoint detection results. We demonstrate the effectiveness of our proposed method on the widely-used CUB200-2011?[.] dataset. The experimental results show that our method can achieve superior accuracy in comparison with the state-of-the-art approaches.作者: 親愛 時(shí)間: 2025-3-30 15:28 作者: 刻苦讀書 時(shí)間: 2025-3-30 19:42
Geometric Context Sensitive Loss and Its Application for Nonrigid Structure from?Motionaditional models. (2) GCS loss can be formulated in both 2D and 3D forms. Thus, the proposed GCS loss is easy to be implemented and can be integrated into current popular 2D/3D coordinates prediction models naturally and effectively, e.g., nonrigid structure from motion. (3) No additional learnable 作者: macabre 時(shí)間: 2025-3-30 21:26 作者: 相信 時(shí)間: 2025-3-31 02:21
Adaptive Underwater Image Enhancement via Color Channel Compensation Based on Optical Restoration anoposed adaptive method fits in versatile scenes adaptively of greenish, bluish and turbid water body producing eye-friendly haze cover removed, color shift corrected, detail enhanced clear result image. Particularly the proposed method highly reduces the reddish effect after execution compared to ma作者: 莎草 時(shí)間: 2025-3-31 08:56 作者: babble 時(shí)間: 2025-3-31 09:44
cal terms in modern Chinese without word segmentation, which avoids word segmentation error spreading to the term alignment. Then we extract English terms according to initial capitalization rules. At last, we align the English and Chinese terms based on co-occurrence frequency and transliteration f作者: 英寸 時(shí)間: 2025-3-31 16:51 作者: tinnitus 時(shí)間: 2025-3-31 20:17 作者: 地名表 時(shí)間: 2025-4-1 01:15
Bangpeng Xiao,Shenyuan Ye,Xicai Li,Min Li,Lingyu Zhang,Yuanqing Wangcal terms in modern Chinese without word segmentation, which avoids word segmentation error spreading to the term alignment. Then we extract English terms according to initial capitalization rules. At last, we align the English and Chinese terms based on co-occurrence frequency and transliteration f作者: Condense 時(shí)間: 2025-4-1 03:39
