作者: 使痛苦 時間: 2025-3-21 20:28 作者: 揭穿真相 時間: 2025-3-22 03:00 作者: PON 時間: 2025-3-22 06:41 作者: Coeval 時間: 2025-3-22 10:11 作者: 泰然自若 時間: 2025-3-22 13:45 作者: 泰然自若 時間: 2025-3-22 19:16
https://doi.org/10.1007/978-3-642-59535-6 tokens and style mappers to learn and transform this editing direction to 3D latent space. To train LAE with multiple attributes, we use directional contrastive loss and style token loss. Furthermore, to ensure view consistency and identity preservation across different poses and attributes, we emp作者: Shuttle 時間: 2025-3-22 23:54 作者: Gum-Disease 時間: 2025-3-23 04:19
https://doi.org/10.1007/978-3-642-59535-6ted extensive experiments on two benchmarks: the low-resolution PKU-DDD17-Car dataset and the high-resolution DSEC dataset. Experimental results show that our method surpasses the state-of-the-art by an impressive margin of . on the DSEC dataset. Besides, our method exhibits significantly better rob作者: 昏暗 時間: 2025-3-23 08:21 作者: 山崩 時間: 2025-3-23 10:44
https://doi.org/10.1007/978-3-642-85538-2Both neural networks are trained using an objective formulated with the aid of self-supervised monocular SLAM on a collection of underwater videos. Thus, our method does not requires any ground-truth color images or caustics labels, and corrects images in real-time. We experimentally demonstrate the作者: CHIDE 時間: 2025-3-23 13:52
https://doi.org/10.1007/978-3-642-85538-2nal datasets, COSTG incorporates not only standard semantic maps but also some textual descriptions of curvilinear object features. To ensure consistency between synthetic semantic maps and images, we introduce the Semantic Consistency Preserving ControlNet (SCP ControlNet). This involves an adaptat作者: 把…比做 時間: 2025-3-23 19:41
https://doi.org/10.1007/978-981-99-3451-5se distributions to their globally balanced and entropy regularized version, which is obtained through a simple self-optimal-transport computation. We ablate and verify our method through a wide set of experiments that show competitive performance with leading methods on both semi-supervised and tra作者: 逗留 時間: 2025-3-24 00:13 作者: exorbitant 時間: 2025-3-24 03:02 作者: arousal 時間: 2025-3-24 09:40
,Few-Shot Image Generation by?Conditional Relaxing Diffusion Inversion, scheduler that progressively introduces perturbations to the SGE, thereby augmenting diversity. Comprehensive experiments demonstrate that our method outperforms GAN-based reconstruction techniques and achieves comparable performance to state-of-the-art (SOTA) FSIG methods. Additionally, it effecti作者: drusen 時間: 2025-3-24 11:08
Data Poisoning Quantization Backdoor Attack,model. The key component is a trigger pattern generator, which is trained together with a surrogate model in an alternating manner. The attack’s effectiveness is tested on multiple benchmark datasets, including CIFAR10, CelebA, and ImageNet10, as well as state-of-the-art backdoor defenses.作者: Visual-Acuity 時間: 2025-3-24 14:54
,DailyDVS-200: A Comprehensive Benchmark Dataset for?Event-Based Action Recognition,equences. This dataset is designed to reflect a broad spectrum of action types, scene complexities, and data acquisition diversity. Each sequence in the dataset is annotated with 14 attributes, ensuring a detailed characterization of the recorded actions. Moreover, DailyDVS-200 is structured to faci作者: synovium 時間: 2025-3-24 19:27 作者: 欺騙手段 時間: 2025-3-25 01:42
,T-CorresNet: Template Guided 3D Point Cloud Completion with?Correspondence Pooling Query Generation the complete point proxies. Finally, we generate the complete point cloud with a FoldingNet following the coarse-to-fine paradigm, according to the fine template and the predicted point proxies. Experimental results demonstrate that our T-CorresNet outperforms the state-of-the-art methods on severa作者: backdrop 時間: 2025-3-25 03:22 作者: 遍及 時間: 2025-3-25 10:13
,Distilling Knowledge from?Large-Scale Image Models for?Object Detection, exhibits sparse query locations, thereby facilitating the distillation process. (2) Considering that large-scale detectors are mainly based on DETRs, we propose a Query Distillation (QD) method specifically tailored for DETRs. The QD performs knowledge distillation by leveraging the spatial positio作者: 破布 時間: 2025-3-25 14:37
,Embracing Events and?Frames with?Hierarchical Feature Refinement Network for?Object Detection,ted extensive experiments on two benchmarks: the low-resolution PKU-DDD17-Car dataset and the high-resolution DSEC dataset. Experimental results show that our method surpasses the state-of-the-art by an impressive margin of . on the DSEC dataset. Besides, our method exhibits significantly better rob作者: Offset 時間: 2025-3-25 16:57 作者: 強制性 時間: 2025-3-25 20:53 作者: corporate 時間: 2025-3-26 01:11 作者: facetious 時間: 2025-3-26 05:51 作者: SAGE 時間: 2025-3-26 09:37
,Identity-Consistent Diffusion Network for?Grading Knee Osteoarthritis Progression in?Radiographic Im generation-guided progression prediction module are introduced. Compared to conventional image-to-image generative models, identity priors regularize and guide the diffusion to focus more on the clinical nuances of the prognosis based on a contrastive learning strategy. The progression prediction 作者: 執(zhí) 時間: 2025-3-26 14:16 作者: reserve 時間: 2025-3-26 18:16 作者: 側(cè)面左右 時間: 2025-3-26 22:18
0302-9743 econstruction, Stereo vision, Computational photography, Neural networks, Image coding, Image reconstruction and Motion estimation..978-3-031-72906-5978-3-031-72907-2Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: Acquired 時間: 2025-3-27 04:06
https://doi.org/10.1007/978-3-642-59535-6property of divergence in our framework contributes to more stable training convergence. Remarkably, our method not only exhibits robustness to corrupted datasets but also achieves superior performance on clean datasets.作者: CORE 時間: 2025-3-27 08:03
Untersuchung der Branntweine und Sprite,n a mixture of object and relationship detection data. Our approach achieves state-of-the-art relationship detection performance on Visual Genome and on the large-vocabulary GQA benchmark at real-time inference speeds. We provide ablations, real-world qualitative examples, and analyses of zero-shot performance.作者: 巧思 時間: 2025-3-27 13:24
https://doi.org/10.1007/978-981-99-3451-5e experiments, showing that our method outperforms state-of-the-art retrieval methods on the new blur-retrieval datasets, which validates the effectiveness of the proposed approach. Code, data, and model are available at ..作者: 救護車 時間: 2025-3-27 15:08
https://doi.org/10.1007/978-3-540-71999-1 than traditional systems?when multiple simulations are run in parallel. To demonstrate the value of our approach we use it as a drop-in replacement for a state-of-the-art classical non-differentiable simulator in an existing video-based 3D human?pose reconstruction framework [.] and show comparable or better accuracy.作者: Euphonious 時間: 2025-3-27 21:09
,A High-Quality Robust Diffusion Framework for?Corrupted Dataset,property of divergence in our framework contributes to more stable training convergence. Remarkably, our method not only exhibits robustness to corrupted datasets but also achieves superior performance on clean datasets.作者: etidronate 時間: 2025-3-27 23:25
Scene-Graph ViT: End-to-End Open-Vocabulary Visual Relationship Detection,n a mixture of object and relationship detection data. Our approach achieves state-of-the-art relationship detection performance on Visual Genome and on the large-vocabulary GQA benchmark at real-time inference speeds. We provide ablations, real-world qualitative examples, and analyses of zero-shot performance.作者: Culmination 時間: 2025-3-28 03:04 作者: 臨時抱佛腳 時間: 2025-3-28 09:06
,Learned Neural Physics Simulation for?Articulated 3D Human Pose Reconstruction, than traditional systems?when multiple simulations are run in parallel. To demonstrate the value of our approach we use it as a drop-in replacement for a state-of-the-art classical non-differentiable simulator in an existing video-based 3D human?pose reconstruction framework [.] and show comparable or better accuracy.作者: CHYME 時間: 2025-3-28 12:04 作者: canvass 時間: 2025-3-28 15:47
,DualBEV: Unifying Dual View Transformation with?Probabilistic Correspondences,orrespondences in one stage, DualBEV effectively bridges the gap between these strategies, harnessing their individual strengths. Our method achieves state-of-the-art performance without Transformer, delivering comparable efficiency to the LSS approach, with 55.2% mAP and 63.4% NDS on the nuScenes test set. Code is available at ..作者: Addictive 時間: 2025-3-28 19:07
Conference proceedings 2025t learning, Object recognition, Image classification, Image processing, Object detection, Semantic segmentation, Human pose estimation, 3D reconstruction, Stereo vision, Computational photography, Neural networks, Image coding, Image reconstruction and Motion estimation..作者: Intervention 時間: 2025-3-28 23:34
,OpenSight: A Simple Open-Vocabulary Framework?for?LiDAR-Based?Object?Detection,ectly transferring existing 2D open-vocabulary models with some known LiDAR classes for open-vocabulary ability, however, tends to suffer from over-fitting problems: The obtained model will detect the known objects, even presented with a novel category. In this paper, we propose OpenSight, a more ad作者: auxiliary 時間: 2025-3-29 06:47 作者: 暴行 時間: 2025-3-29 07:38 作者: febrile 時間: 2025-3-29 12:29
,DailyDVS-200: A Comprehensive Benchmark Dataset for?Event-Based Action Recognition,range, minimal latency, and energy efficiency, setting them apart from conventional frame-based cameras. The distinctive capabilities of event cameras have ignited significant interest in the domain of event-based action recognition, recognizing their vast potential for advancement. However, the dev作者: ALIEN 時間: 2025-3-29 18:44
,On the?Topology Awareness and?Generalization Performance of?Graph Neural Networks,nant tool for learning representations of graph-structured data. A key feature of GNNs is their use of graph structures as input, enabling them to exploit the graphs’ inherent topological properties—known as the topology awareness of GNNs. Despite the empirical successes of GNNs, the influence of to作者: STIT 時間: 2025-3-29 21:07
,T-CorresNet: Template Guided 3D Point Cloud Completion with?Correspondence Pooling Query Generations often suffer from incompleteness due to limited perspectives, scanner resolution and occlusion. Therefore the prediction of missing parts performs a crucial task. In this paper, we propose a novel method for point cloud completion. We utilize a spherical template to guide the generation of the coa作者: Postulate 時間: 2025-3-30 03:06 作者: 符合你規(guī)定 時間: 2025-3-30 06:58 作者: 發(fā)電機 時間: 2025-3-30 08:19 作者: 發(fā)展 時間: 2025-3-30 14:03 作者: Nucleate 時間: 2025-3-30 17:05 作者: Kidney-Failure 時間: 2025-3-30 21:37
Scene-Graph ViT: End-to-End Open-Vocabulary Visual Relationship Detection,ship modules or decoders to existing object detection architectures. This separation increases complexity and hinders end-to-end training, which limits performance. We propose a simple and highly efficient decoder-free architecture for open-vocabulary visual relationship detection. Our model consist作者: 知識 時間: 2025-3-31 03:00
,Self-Supervised Underwater Caustics Removal and?Descattering via?Deep Monocular SLAM,h as caustic caused by sunlight refracting on a wavy surface. These challenges impede widespread use of computer vision tools that could aid in ecological surveying of underwater environments or in industrial applications. Existing algorithms for alleviating caustics and descattering the image to re作者: 不透明 時間: 2025-3-31 08:17 作者: 過于平凡 時間: 2025-3-31 10:00
,Retrieval Robust to?Object Motion Blur,explored area in computer vision, it primarily focuses on sharp and static objects, and retrieval of motion-blurred objects in large image collections remains unexplored. We propose a method for object retrieval in images that are affected by motion blur. The proposed method learns a robust represen作者: 前面 時間: 2025-3-31 16:16
,Unsupervised Representation Learning by?Balanced Self Attention Matching, of the instance discrimination task, whose optimization is known to be prone to instabilities that can lead to feature collapse. Different techniques have been devised to circumvent this issue, including the use of negative pairs with different contrastive losses, the use of external memory banks, 作者: 吹牛需要藝術(shù) 時間: 2025-3-31 18:19
,DualBEV: Unifying Dual View Transformation with?Probabilistic Correspondences,y employs resource-intensive Transformer to establish robust correspondences between 3D and 2D features, while the 2D-to-3D VT utilizes the Lift-Splat-Shoot (LSS) pipeline for real-time application, potentially missing distant information. To address these limitations, we propose DualBEV, a unified 作者: cardiopulmonary 時間: 2025-3-31 23:39
,Identity-Consistent Diffusion Network for?Grading Knee Osteoarthritis Progression in?Radiographic Ir-aided techniques to automatically assess the severity and progression of KOA can greatly benefit KOA treatment and disease management. Particularly, the advancement of X-ray technology in KOA demonstrates its potential for this purpose. Yet, existing X-ray prognosis research generally yields a sin作者: Constituent 時間: 2025-4-1 02:46
,Learned Neural Physics Simulation for?Articulated 3D Human Pose Reconstruction,nvenient alternative to traditional physics simulators for use in computer vision tasks such as human motion reconstruction from video. To that end we introduce a training procedure and model components that support the construction of a recurrent neural architecture to accurately learn to simulate 作者: hemoglobin 時間: 2025-4-1 07:50
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/242303.jpg作者: 錯誤 時間: 2025-4-1 11:04 作者: 細節(jié) 時間: 2025-4-1 16:12
J. C. Braekman,D. Daloze,J. M. Pasteelsimal samples poses a significant challenge. This requires a method that can both capture the broad diversity and the true characteristics of the target domain distribution. We present . (CRDI), an innovative ‘training-free’ approach designed to enhance distribution diversity in synthetic image gener作者: Afflict 時間: 2025-4-1 22:22 作者: GILD 時間: 2025-4-2 01:20
https://doi.org/10.1007/978-1-4757-2905-4range, minimal latency, and energy efficiency, setting them apart from conventional frame-based cameras. The distinctive capabilities of event cameras have ignited significant interest in the domain of event-based action recognition, recognizing their vast potential for advancement. However, the dev
