作者: 收藏品 時(shí)間: 2025-3-21 22:15
Lecture Notes in Computer Scienceworks for this task often rely on external tasks, ., pose estimation, or semantic segmentation, to extract local features over fixed given regions. However, these external models may perform poorly on Occluded ReID, since they are still open problems with no reliable performance guarantee and are no作者: 上腭 時(shí)間: 2025-3-22 01:00 作者: promote 時(shí)間: 2025-3-22 06:00
Advances in Cryptology – CRYPTO 2021its embedding space. Despite recent advances in deep metric learning, it remains challenging for the learned metric to generalize to unseen classes with a substantial domain gap. To tackle the issue, we explore a new problem of few-shot metric learning that aims to adapt the embedding function to th作者: Bereavement 時(shí)間: 2025-3-22 08:56 作者: 硬化 時(shí)間: 2025-3-22 12:53 作者: 硬化 時(shí)間: 2025-3-22 20:54
https://doi.org/10.1007/978-3-031-15985-5hat jointly detect and recognize scene text have been proposed in recent years. In this paper, we present a novel end-to-end text spotting network SPRNet for arbitrary-shaped scene text. We propose a parametric B-spline centerline-based representation model to describe the distinctive global shape c作者: 自傳 時(shí)間: 2025-3-22 22:34
Allen Kim,Xiao Liang,Omkant Pandeyoxes updated in the cascaded training manner. However, due to the sparse nature and the one-to-one relation between the query and its attending region, it heavily depends on the self attention, which is usually inaccurate in the early training stage. Moreover, in a scene of dense objects, the object作者: Armada 時(shí)間: 2025-3-23 04:32
Lecture Notes in Computer Sciencence in low-resolution face images with a pixel width of 50 pixels or less. To solve a limitation under the challenging low-resolution conditions, we propose a high-frequency attentive super-resolved gaze estimation network, i.e., HAZE-Net. Our network improves the resolution of the input image and e作者: 冰河期 時(shí)間: 2025-3-23 09:09 作者: 灌輸 時(shí)間: 2025-3-23 12:15 作者: 令人發(fā)膩 時(shí)間: 2025-3-23 14:38 作者: anthesis 時(shí)間: 2025-3-23 21:35
Zhenzhen Bao,Jian Guo,Danping Shi,Yi Tuserve that existing models take into account the respective advantages of the two modalities but do not fully explore the roles of cross-modality features of various levels. To this end, we remodel the relationship between RGB features and depth features from a new perspective of the feature encodin作者: Proclaim 時(shí)間: 2025-3-23 23:13 作者: 死亡率 時(shí)間: 2025-3-24 03:12
Semi-quantum Tokenized Signaturesworks have been hampered by (1) insufficient data similarity mining based on global-only image representations, and (2) the hash code semantic loss caused by the data augmentation. In this paper, we propose a novel method, namely Weighted Contrative Hashing (WCH), to take a step towards solving thes作者: Default 時(shí)間: 2025-3-24 06:32
Xiaoyang Dong,Jian Guo,Shun Li,Phuong Phamthe target content usually scatters over the whole image, and they are indiscernible from the background. Thus, it is difficult to learn feature representation that focuses on these contents, rendering CVGL a challenging and unsolved task. In this work, we design a Content-Aware Hierarchical Represe作者: Predigest 時(shí)間: 2025-3-24 14:29 作者: 品牌 時(shí)間: 2025-3-24 15:15 作者: LINE 時(shí)間: 2025-3-24 22:07
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/234138.jpg作者: mastoid-bone 時(shí)間: 2025-3-25 01:58
Computer Vision – ACCV 2022978-3-031-26348-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 小口啜飲 時(shí)間: 2025-3-25 07:15
https://doi.org/10.1007/978-3-031-26348-4artificial intelligence; computer networks; computer systems; computer vision; databases; image analysis; 作者: 表臉 時(shí)間: 2025-3-25 10:19
978-3-031-26347-7The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 無(wú)聊點(diǎn)好 時(shí)間: 2025-3-25 12:32 作者: capillaries 時(shí)間: 2025-3-25 17:33
Conference proceedings 2023cember 2022...The total of 277 contributions included in the proceedings set was carefully reviewed and selected from 836 submissions during two rounds of reviewing and improvement. The papers focus on the following topics:..Part I: 3D computer vision; optimization methods;.Part II: applications of 作者: ethereal 時(shí)間: 2025-3-25 22:48 作者: 起波瀾 時(shí)間: 2025-3-26 03:50
Lecture Notes in Computer Scienceion of faces to approximate head pose. The experimental results indicate that the proposed method exhibits robust gaze estimation performance even in low-resolution face images with 28.28 pixels. The source code of this work is available at ..作者: 裝勇敢地做 時(shí)間: 2025-3-26 07:27 作者: originality 時(shí)間: 2025-3-26 11:13
Few-shot Metric Learning: Online Adaptation of?Embedding for?Retrievalset, .DeepFashion, demonstrate that our method consistently improves the learned metric by adapting it to target classes and achieves a greater gain in image retrieval when the domain gap from the source classes is larger.作者: 先行 時(shí)間: 2025-3-26 13:21
HAZE-Net: High-Frequency Attentive Super-Resolved Gaze Estimation in?Low-Resolution Face Imagesion of faces to approximate head pose. The experimental results indicate that the proposed method exhibits robust gaze estimation performance even in low-resolution face images with 28.28 pixels. The source code of this work is available at ..作者: 使乳化 時(shí)間: 2025-3-26 17:21
Continuous Self-study: Scene Graph Generation with?Self-knowledge Distillation and?Spatial Augmentathod is adopted to augment spatial features and supplement relationship information. On the Visual Genome benchmark, experiments show that the proposed CSS achieves obvious improvements over the previous state-of-the-art methods. Our code is available at ..作者: Tracheotomy 時(shí)間: 2025-3-26 21:03 作者: tenuous 時(shí)間: 2025-3-27 01:44
0302-9743 art VII: generative models for computer vision; segmentation and grouping; motion and tracking; document image analysis; big data, large scale methods. .978-3-031-26347-7978-3-031-26348-4Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: infringe 時(shí)間: 2025-3-27 08:36
Which E-Voting Problems Do We Need to Solve?ales and locations, and learn image relations by giving the highest weights to the best matching pairs. The SM is trained to activate the most related locations and scales between support and query data. We apply and evaluate SM on various few-shot learning models and backbones for comprehensive eva作者: Atheroma 時(shí)間: 2025-3-27 12:12
Lecture Notes in Computer Scienceuth occlusion annotations, we measure the occlusion of landmarks by the awareness scores, when referring to a memorized dictionary storing average landmark features. These awareness scores are then used as a soft weight for training and inferring. Meanwhile, the memorized dictionary is momenta updat作者: reaching 時(shí)間: 2025-3-27 15:33 作者: 偽善 時(shí)間: 2025-3-27 20:07 作者: 政府 時(shí)間: 2025-3-27 23:05
https://doi.org/10.1007/978-3-030-84259-8ginal implementation of the modern object detection algorithms and applying simple fine-tuning, we can improve the rotation robustness of these original detection algorithms while inheriting modern network architectures’ strengths. Our framework overwhelmingly outperforms typical geometric data augm作者: remission 時(shí)間: 2025-3-28 04:52
https://doi.org/10.1007/978-3-031-15985-5mpetitive text spotting performance on standard benchmarks through a simple architecture equipped with the proposed text representation and rectification mechanism, which demonstrates the effectiveness of the method in detecting and recognizing scene text with arbitrary shapes.作者: cushion 時(shí)間: 2025-3-28 06:57 作者: 窩轉(zhuǎn)脊椎動(dòng)物 時(shí)間: 2025-3-28 13:19 作者: 生銹 時(shí)間: 2025-3-28 16:45 作者: 嚴(yán)峻考驗(yàn) 時(shí)間: 2025-3-28 20:32 作者: 浮雕 時(shí)間: 2025-3-29 02:58 作者: SAGE 時(shí)間: 2025-3-29 04:41
Advances in Cryptology – CRYPTO 2022ures within an RoI. These discriminative relation features are further enriched by introducing a spatio-channel attention where the foreground and background discriminability is empowered in a joint spatio-channel space. Our ARM module is generic and it does not rely on fine-grained supervisions or 作者: 暗指 時(shí)間: 2025-3-29 08:16
Semi-quantum Tokenized Signaturesistilled to facilitate the hash codes learning with a distillation loss, so as to obtain better retrieval performance. Extensive experiments show that the proposed WCH significantly outperforms existing unsupervised hashing methods on three benchmark datasets. Code is available at: ..作者: 膽小鬼 時(shí)間: 2025-3-29 11:50 作者: 情感 時(shí)間: 2025-3-29 19:09 作者: Orgasm 時(shí)間: 2025-3-29 20:04 作者: 種族被根除 時(shí)間: 2025-3-30 03:27
AONet: Attentional Occlusion-Aware Network for?Occluded Person Re-identificationuth occlusion annotations, we measure the occlusion of landmarks by the awareness scores, when referring to a memorized dictionary storing average landmark features. These awareness scores are then used as a soft weight for training and inferring. Meanwhile, the memorized dictionary is momenta updat作者: 供過(guò)于求 時(shí)間: 2025-3-30 06:41
FFD Augmentor: Towards Few-Shot Oracle Character Recognition from?Scratchms to directly enlarge the size of training data to help the training of deep models. But popular augment strategies, such as dividing the characters into stroke sequences, break the orthographic units of Chinese characters and destroy the semantic information. Thus simply adding noise to strokes pe作者: 構(gòu)想 時(shí)間: 2025-3-30 10:51
3D Shape Temporal Aggregation for?Video-Based Clothing-Change Person Re-identificationodule. It embeds the identity information into the generation of 3D shapes by the joint learning of shape estimation and identity recognition. Second, a difference-aware shape aggregation module is designed to measure inter-frame 3D human shape differences and automatically select the unique 3D shap作者: 摻假 時(shí)間: 2025-3-30 14:45 作者: 冷淡周邊 時(shí)間: 2025-3-30 19:44 作者: transient-pain 時(shí)間: 2025-3-30 21:19
IoU-Enhanced Attention for?End-to-End Task Specific Object Detectionlassification and regression, we add two lightweight projection heads to provide the dynamic channel masks based on object query, and they multiply with the output from dynamic convs, making the results suitable for the two different tasks. We validate the proposed scheme on different datasets, incl作者: blithe 時(shí)間: 2025-3-31 03:40 作者: 恫嚇 時(shí)間: 2025-3-31 08:24
Cross-Architecture Knowledge Distillationeme is further presented to improve the robustness and stability of the framework. Extensive experiments show that the proposed method outperforms 14 state-of-the-arts on both small-scale and large-scale datasets.作者: 枯萎將要 時(shí)間: 2025-3-31 11:57
Cross-Domain Local Characteristic Enhanced Deepfake Video Detection forgery-sensitive local regions of a human face to guide the model to enhance subtle artifacts and localize potential anomalies. Extensive experiments on several benchmark datasets demonstrate the impressive performance of our method, and we achieve superiority over several state-of-the-art methods作者: 中子 時(shí)間: 2025-3-31 13:23 作者: aneurysm 時(shí)間: 2025-3-31 20:29 作者: 驕傲 時(shí)間: 2025-3-31 23:47
