作者: 做方舟 時(shí)間: 2025-3-21 21:01
Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/242349.jpg作者: 哀求 時(shí)間: 2025-3-22 02:35
https://doi.org/10.1007/978-3-031-72949-2artificial intelligence; computer networks; computer systems; computer vision; education; Human-Computer 作者: legislate 時(shí)間: 2025-3-22 05:39 作者: 情感脆弱 時(shí)間: 2025-3-22 10:52 作者: CIS 時(shí)間: 2025-3-22 16:11 作者: CIS 時(shí)間: 2025-3-22 17:20 作者: 延期 時(shí)間: 2025-3-23 00:14 作者: 笨拙的我 時(shí)間: 2025-3-23 03:06
Jessica E. Young,Lawrence S. B. Goldstein Semi-supervised domain generalization has been proposed very recently to combat this challenge?by leveraging limited labeled data along with abundant unlabeled?data collected from multiple medical institutions, depending on precisely harnessing unlabeled data while improving generalization simultan作者: Pander 時(shí)間: 2025-3-23 07:23
https://doi.org/10.1007/978-1-0716-2655-9 has prospered recently, how?to bind the predicted 3D occupancy grids with open-world semantics still remains under-explored due to limited open-world annotations. Hence, instead of building our model from scratch, we try to?blend 2D foundation models, specifically a depth model MiDaS and?a semantic作者: 斜 時(shí)間: 2025-3-23 13:32 作者: Accomplish 時(shí)間: 2025-3-23 13:51 作者: Conducive 時(shí)間: 2025-3-23 20:52
Jessica E. Young,Lawrence S. B. Goldsteinlenge of domain shift, impacting?the generalization performance of existing FAS methods. In this paper, we rethink about the inherence of domain shift and deconstruct?it into two factors: image style and image quality. Quality influences the purity of the presentation of spoof information, while?sty作者: 失敗主義者 時(shí)間: 2025-3-24 02:08 作者: DEMN 時(shí)間: 2025-3-24 06:01 作者: Graphite 時(shí)間: 2025-3-24 07:08 作者: Munificent 時(shí)間: 2025-3-24 11:32 作者: cocoon 時(shí)間: 2025-3-24 16:41 作者: 遺傳 時(shí)間: 2025-3-24 20:58 作者: biopsy 時(shí)間: 2025-3-25 01:49 作者: Digitalis 時(shí)間: 2025-3-25 07:06
https://doi.org/10.1007/978-3-7091-3396-5oad implications for content creators and recommendation systems. This study delves deep into the intricacies of predicting engagement for newly published videos with limited user interactions. Surprisingly, our findings reveal that Mean Opinion Scores from previous video quality assessment datasets作者: Misgiving 時(shí)間: 2025-3-25 07:58
https://doi.org/10.1007/978-3-0348-6370-4ons that bias classifiers. This problem is often aggravated by discrepancies between labeled and unlabeled class distributions, leading to biased pseudo-labels, neglect of rare classes, and poorly calibrated probabilities. To address these issues, we introduce Flexible Distribution Alignment (FlexDA作者: Latency 時(shí)間: 2025-3-25 15:41
Ein Streifzug durch das Universumiously learned information, when presented with a new task. CL aims to instill the lifelong learning characteristic of humans in intelligent systems, making them capable of learning continuously while retaining what was already learned. Current CL problems involve either learning new domains (domain作者: 頑固 時(shí)間: 2025-3-25 18:38 作者: institute 時(shí)間: 2025-3-25 21:10 作者: 自作多情 時(shí)間: 2025-3-26 03:50
,Retargeting Visual Data with?Deformation Fields,is technique applies to different kinds of visual data, including images, 3D scenes given as neural radiance fields, or even polygon meshes. Experiments conducted on different visual data show that our method achieves better content-aware retargeting compared to previous methods.作者: grotto 時(shí)間: 2025-3-26 07:36 作者: Pericarditis 時(shí)間: 2025-3-26 08:48 作者: 公共汽車 時(shí)間: 2025-3-26 12:54
Conference proceedings 2025ter Vision, ECCV 2024, held in Milan, Italy, during September 29–October 4, 2024...The 2387 papers presented in these proceedings were carefully reviewed and selected from a total of 8585 submissions. They deal with topics such as Computer vision, Machine learning, Deep neural networks, Reinforcemen作者: Vo2-Max 時(shí)間: 2025-3-26 17:08
,FARSE-CNN: Fully Asynchronous, Recurrent and?Sparse Event-Based CNN,both in space and time. We theoretically derive the complexity of all components in our architecture,?and experimentally validate our method on tasks for object recognition, object detection and gesture recognition. FARSE-CNN achieves similar or better performance than the state-of-the-art among asy作者: 競(jìng)選運(yùn)動(dòng) 時(shí)間: 2025-3-26 21:40 作者: output 時(shí)間: 2025-3-27 01:08 作者: 分散 時(shí)間: 2025-3-27 05:27
,Event-Aided Time-to-Collision Estimation for?Autonomous Driving,linear optimization problem. Experiments on both synthetic and real data demonstrate the effectiveness of the proposed method, outperforming other alternative methods in terms of efficiency and accuracy. Dataset used in this paper can be found at ..作者: 拱墻 時(shí)間: 2025-3-27 10:29
,The Devil Is in?the?Statistics: Mitigating and?Exploiting Statistics Difference for?Generalizable S statistics-aggregated branch for domain-invariant feature learning. Furthermore, to simulate unseen domains with statistics difference, we approach this from two aspects, ., a perturbation?with histogram matching at image level and a random batch normalization selection strategy at feature level, p作者: palette 時(shí)間: 2025-3-27 14:23
VEON: Vocabulary-Enhanced Occupancy Prediction,ong-tail problem. To address these issues, we propose VEON?for .ocabulary-.nhanced .ccupancy predictio. by not only assembling but also adapting?these foundation models. We first equip MiDaS with a Zoedepth head?and low-rank adaptation (LoRA) for relative-metric-bin?depth transformation while reserv作者: 婚姻生活 時(shí)間: 2025-3-27 19:05
,Adapt Without Forgetting: Distill Proximity from?Dual Teachers in?Vision-Language Models, sample. Experimental results demonstrate a considerable improvement over existing methodologies, which illustrate the effectiveness?of the proposed method in the field of continual learning. Code?is available?at ..作者: ORE 時(shí)間: 2025-3-27 23:41
,The Sky’s the?Limit: Relightable Outdoor Scenes via?a?Sky-Pixel Constrained Illumination Prior and?g gradients from appearance loss to flow?from shadows to influence the estimation of illumination and geometry. Our method estimates high-quality albedo, geometry, illumination?and sky visibility, achieving state-of-the-art results on the NeRF-OSR relighting benchmark. Our code and models can be fou作者: 懶惰民族 時(shí)間: 2025-3-28 05:29 作者: fidelity 時(shí)間: 2025-3-28 08:43
,Hetecooper: Feature Collaboration Graph for?Heterogeneous Collaborative Perception,sformer is designed to transfer feature messages in the feature collaboration graph. Firstly, the number of?node channels and the semantic space are unified by the semantic mapper. Then, the feature information is aggregated by the edge weight guided attention, and finally the fusion of heterogeneou作者: Mumble 時(shí)間: 2025-3-28 12:10
Learning-based Axial Video Motion Magnification,specific axes are critical, by providing simplified and easily readable motion information. To achieve this, we propose a novel Motion Separation Module that enables the disentangling and magnifying of motion representation along axes of interest. Furthermore, we build a new synthetic training datas作者: 欄桿 時(shí)間: 2025-3-28 18:11 作者: Ambulatory 時(shí)間: 2025-3-28 20:07
,Class-Incremental Learning with?CLIP: Adaptive Representation Adjustment and?Parameter Fusion, fusion to further mitigate forgetting during adapter module fine-tuning. Experiments on several conventional benchmarks show that our method achieves state-of-the-art results. Our code is available at ..作者: 機(jī)警 時(shí)間: 2025-3-29 01:25 作者: 來這真柔軟 時(shí)間: 2025-3-29 04:38 作者: 轉(zhuǎn)向 時(shí)間: 2025-3-29 08:59
,Delving Deep into Engagement Prediction of?Short Videos,al content, background music, and text data, are investigated to enhance engagement prediction. With the proposed dataset and two key metrics, our method demonstrates its ability to predict engagements of short videos purely from video content.作者: 法律 時(shí)間: 2025-3-29 15:11
,Flexible Distribution Alignment: Towards Long-Tailed Semi-supervised Learning with?Proper Calibrati proves robust against label shift, significantly improves model calibration in LTSSL contexts, and surpasses previous state-of-of-art approaches across multiple benchmarks, including CIFAR100-LT, STL10-LT, and ImageNet127, addressing class imbalance challenges in semi-supervised learning. Our code 作者: Ringworm 時(shí)間: 2025-3-29 16:06
,CLEO: Continual Learning of?Evolving Ontologies,ver time, such as those in autonomous driving. We use Cityscapes, PASCAL VOC, and Mapillary Vistas to define the task settings and demonstrate the applicability of CLEO. We highlight the shortcomings of existing CIL methods in adapting to CLEO and propose a baseline solution, called Modelling Ontolo作者: 終點(diǎn) 時(shí)間: 2025-3-29 22:45
Advocacy for Persons with Senile Dementiaboth in space and time. We theoretically derive the complexity of all components in our architecture,?and experimentally validate our method on tasks for object recognition, object detection and gesture recognition. FARSE-CNN achieves similar or better performance than the state-of-the-art among asy作者: Forage飼料 時(shí)間: 2025-3-30 02:04 作者: 遺棄 時(shí)間: 2025-3-30 07:44
Vijaya L. Melnick,Nancy Neveloff Dublerrompt Learning, utilizing multiple context-specific prompts for text embeddings to capture diverse class representations across masks. Overall, MTA-CLIP achieves state-of-the-art, surpassing prior works by an average of 2.8% and 1.3% on standard benchmark datasets, ADE20k and Cityscapes, respectivel作者: inventory 時(shí)間: 2025-3-30 11:53
Pamela B. Hoffman,Leslie S. Libowlinear optimization problem. Experiments on both synthetic and real data demonstrate the effectiveness of the proposed method, outperforming other alternative methods in terms of efficiency and accuracy. Dataset used in this paper can be found at ..作者: sparse 時(shí)間: 2025-3-30 16:28 作者: 重畫只能放棄 時(shí)間: 2025-3-30 16:36
https://doi.org/10.1007/978-1-0716-2655-9ong-tail problem. To address these issues, we propose VEON?for .ocabulary-.nhanced .ccupancy predictio. by not only assembling but also adapting?these foundation models. We first equip MiDaS with a Zoedepth head?and low-rank adaptation (LoRA) for relative-metric-bin?depth transformation while reserv作者: 危險(xiǎn) 時(shí)間: 2025-3-30 23:18
https://doi.org/10.1007/978-1-0716-2655-9 sample. Experimental results demonstrate a considerable improvement over existing methodologies, which illustrate the effectiveness?of the proposed method in the field of continual learning. Code?is available?at ..作者: 平庸的人或物 時(shí)間: 2025-3-31 01:42
Jessica E. Young,Lawrence S. B. Goldsteing gradients from appearance loss to flow?from shadows to influence the estimation of illumination and geometry. Our method estimates high-quality albedo, geometry, illumination?and sky visibility, achieving state-of-the-art results on the NeRF-OSR relighting benchmark. Our code and models can be fou作者: 不能根除 時(shí)間: 2025-3-31 05:49
Jessica E. Young,Lawrence S. B. Goldsteinining consistency between?live and spoof face identities, which can also alleviate the scarcity?of labeled data with novel type attacks faced by nowadays FAS system. We demonstrate the effectiveness of our framework on challenging cross-domain and cross-attack FAS datasets, achieving?the state-of-th作者: LINE 時(shí)間: 2025-3-31 12:16 作者: 召集 時(shí)間: 2025-3-31 14:53
https://doi.org/10.1007/978-1-59259-661-4specific axes are critical, by providing simplified and easily readable motion information. To achieve this, we propose a novel Motion Separation Module that enables the disentangling and magnifying of motion representation along axes of interest. Furthermore, we build a new synthetic training datas作者: NOMAD 時(shí)間: 2025-3-31 20:02
Ramon Diaz-Arrastia,Fred Baskinw that it actually outperforms most of the previous SFOD methods. Additionally, we showcase that an even simpler strategy consisting in training on a fixed set of pseudo-labels can achieve similar performance to the more complex teacher-student mutual learning, while being computationally efficient 作者: lymphoma 時(shí)間: 2025-4-1 01:31 作者: 一加就噴出 時(shí)間: 2025-4-1 02:56
Konrad Maurer,Peter Riederer,Helmut Beckmanns and forms more representative clusters. We then perform bag-level prediction with another Dirichlet process model on the bags, which imposes a natural regularization on learning to prevent overfitting and enhance generalizability. Moreover, as a Bayesian nonparametric method, the cDP model can acc作者: 間接 時(shí)間: 2025-4-1 07:58
S. Flament,A. Delacourte,A. Défossezrning to enforce semantic consistency constraints across sequences from the same subject. Our approach has demonstrated significant performance improvements on challenging datasets, proving its effectiveness. Moreover, it can be seamlessly integrated into existing gait recognition methods.作者: 注意力集中 時(shí)間: 2025-4-1 11:04
https://doi.org/10.1007/978-3-7091-3396-5al content, background music, and text data, are investigated to enhance engagement prediction. With the proposed dataset and two key metrics, our method demonstrates its ability to predict engagements of short videos purely from video content.
