作者: Iniquitous 時(shí)間: 2025-3-21 20:15 作者: OUTRE 時(shí)間: 2025-3-22 03:22
https://doi.org/10.1007/978-3-031-73220-1artificial intelligence; computer networks; computer systems; computer vision; education; Human-Computer 作者: 閑聊 時(shí)間: 2025-3-22 08:15
978-3-031-73219-5The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 音樂等 時(shí)間: 2025-3-22 10:24 作者: detach 時(shí)間: 2025-3-22 15:27 作者: detach 時(shí)間: 2025-3-22 17:23 作者: Incommensurate 時(shí)間: 2025-3-23 00:19
Sü?wasser-Aquarien und Terrarients often operate within their limited domains, leading to a ‘domain shift’ across clients. Privacy concerns limit each client’s learning to its own domain data, which increase the risk of overfitting. Moreover, the process of aggregating models trained on own limited domain can be potentially lead t作者: COWER 時(shí)間: 2025-3-23 05:07
,Die Abh?ngigkeit einiger Fermente vom pH,, intrinsically linked to camera pose and scene geometry, it is typically treated as a 2D problem. This makes sense as the goal of matching is to establish correspondences between 2D pixel fields, but also seems like a potentially hazardous choice. In this work, we take a different stance and propos作者: 仇恨 時(shí)間: 2025-3-23 06:08 作者: intelligible 時(shí)間: 2025-3-23 09:52
https://doi.org/10.1007/978-3-642-47418-7enes still poses a challenge due to their complex geometric structures and unconstrained dynamics. Without the help of 3D motion cues, previous methods often require simplified setups with slow camera motion and only a few/single dynamic actors, leading to suboptimal solutions in most urban setups. 作者: 評(píng)論者 時(shí)間: 2025-3-23 17:02 作者: 勤勞 時(shí)間: 2025-3-23 22:00
Emotion, Motivation und Volition,and task labels are spuriously correlated (e.g., “grassy background” and “cows”). Existing bias mitigation methods that aim to address this issue often either rely on group labels for training or validation, or require an extensive hyperparameter search. Such data and computational requirements hind作者: 苦笑 時(shí)間: 2025-3-23 23:25 作者: 集中營 時(shí)間: 2025-3-24 04:49
S?tze und Texte verstehen und produzierenes dealing with the generation of 4D dynamic shapes that have the form of 3D objects deforming over time. To bridge this gap, we focus on generating 4D dynamic shapes with an emphasis on both generation quality and efficiency in this paper. HyperDiffusion, a previous work on 4D generation, proposed 作者: 污穢 時(shí)間: 2025-3-24 07:12 作者: refraction 時(shí)間: 2025-3-24 14:45
Multisensorische Informationsverarbeitungfor every pixel. This is challenging as a uniform representation may not account for the complex and diverse motion and appearance of natural videos. We address this problem and propose a new test-time optimization method, named DecoMotion, for estimating per-pixel and long-range motion. DecoMotion 作者: 感染 時(shí)間: 2025-3-24 18:37 作者: Conjuction 時(shí)間: 2025-3-24 19:16 作者: 到婚嫁年齡 時(shí)間: 2025-3-25 02:55 作者: 后天習(xí)得 時(shí)間: 2025-3-25 03:26 作者: 移植 時(shí)間: 2025-3-25 09:02
Christian Becker-Carus,Mike Wendteal surgical scenarios. Although a few works have explored single-image real-world desmoking in unpaired learning manners, they still encounter challenges in handling dense smoke. In this work, we address these issues together by introducing the self-supervised surgery video desmoking (SelfSVD). On 作者: confederacy 時(shí)間: 2025-3-25 15:26 作者: 我悲傷 時(shí)間: 2025-3-25 16:12
https://doi.org/10.1007/978-3-642-75228-5aluate Chains against a new benchmark for complex multi-human scene synthesis, showing superior performance in human quality and scene accuracy over existing methods. Remarkably, Chains achieves this with?under 0.45?s for a 20-step inference, demonstrating?both effectiveness and efficiency.作者: Chivalrous 時(shí)間: 2025-3-25 21:57
,Chains of?Diffusion Models,aluate Chains against a new benchmark for complex multi-human scene synthesis, showing superior performance in human quality and scene accuracy over existing methods. Remarkably, Chains achieves this with?under 0.45?s for a 20-step inference, demonstrating?both effectiveness and efficiency.作者: Senescent 時(shí)間: 2025-3-26 00:58
Conference proceedings 2025nt 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; motion estimation..作者: DEBT 時(shí)間: 2025-3-26 04:52
0302-9743 reconstruction; stereo vision; computational photography; neural networks; image coding; image reconstruction; motion estimation..978-3-031-73219-5978-3-031-73220-1Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: 根除 時(shí)間: 2025-3-26 09:13
Ph. Broemser,E. Th. Brücke,H. Wintersteinons. Last, we employ a segmentation method to compare CLIP distances among the segmented components, ultimately selecting the most promising object from the sampled subset. Extensive experiments demonstrate that our approach outperforms recent SOTA T2I methods. Surprisingly, our results even rival those of human artists, such as . in Fig.?.. 作者: enflame 時(shí)間: 2025-3-26 13:11
Emotion, Motivation und Volition,er-free framework that leverages the . training history of a helper model to identify spurious samples, and . a group-balanced training set from which a robust model can be trained. We show that TAB improves worst-group performance without . group information or model selection, outperforming existing methods while maintaining overall accuracy.作者: 低能兒 時(shí)間: 2025-3-26 18:25 作者: Coronation 時(shí)間: 2025-3-27 00:18
TP2O: Creative Text Pair-to-Object Generation Using Balance Swap-Sampling,ons. Last, we employ a segmentation method to compare CLIP distances among the segmented components, ultimately selecting the most promising object from the sampled subset. Extensive experiments demonstrate that our approach outperforms recent SOTA T2I methods. Surprisingly, our results even rival those of human artists, such as . in Fig.?.. 作者: 舊石器 時(shí)間: 2025-3-27 01:48
Efficient Bias Mitigation Without Privileged Information,er-free framework that leverages the . training history of a helper model to identify spurious samples, and . a group-balanced training set from which a robust model can be trained. We show that TAB improves worst-group performance without . group information or model selection, outperforming existing methods while maintaining overall accuracy.作者: jovial 時(shí)間: 2025-3-27 05:56 作者: narcissism 時(shí)間: 2025-3-27 13:11 作者: Amnesty 時(shí)間: 2025-3-27 13:49
0302-9743 ce on Computer 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; r作者: 冷淡周邊 時(shí)間: 2025-3-27 20:01
,Robust Nearest Neighbors for?Source-Free Domain Adaptation Under Class Distribution Shift,ng additional generic features free of the source model’s CDS bias. This provides a “second-opinion” regarding which nearest neighbors are more suitable for adaptation. We evaluate our method?using various types of features, datasets and tasks, outperforming previous methods in SFDA under CDS. Our c作者: 種屬關(guān)系 時(shí)間: 2025-3-27 22:52
,Time-Efficient and?Identity-Consistent Virtual Try-On Using A Variant of?Altered Diffusion Models,dividual features and a try-on module refining the attire?and generating missing parts integrated with a mask-aware post-processing technique ensuring the integrity of the individual’s identity. It demonstrates impressive results, surpassing?the state-of-the-art in speed by nearly 20 times during in作者: 宮殿般 時(shí)間: 2025-3-28 02:42
,Feature Diversification and?Adaptation for?Federated Domain Generalization,while preserving privacy. Our resultant global model shows robust performance on unseen test domain data. To enhance performance further, we develop an instance-adaptive inference approach tailored for test domain data. Our proposed instance feature adapter dynamically adjusts feature statistics to 作者: 修正案 時(shí)間: 2025-3-28 08:10 作者: Between 時(shí)間: 2025-3-28 13:13
,RoDUS: Robust Decomposition of?Static and?Dynamic Elements in?Urban Scenes, the reconstructed background, all by using self-supervision. Notably, experimental evaluations on KITTI-360 and Pandaset datasets demonstrate the effectiveness of our method in decomposing challenging urban scenes into precise static and dynamic components.作者: 使出神 時(shí)間: 2025-3-28 14:49
,RecurrentBEV: A Long-Term Temporal Fusion Framework for?Multi-view 3D Detection, fusion ability while still enjoying efficient inference latency and memory consumption during inference. Extensive experiments on the nuScenes benchmark demonstrate its effectiveness, achieving a new state-of-the-art performance of 57.4. mAP and 65.1. NDS on the test set. The real-time version (25.作者: 分發(fā) 時(shí)間: 2025-3-28 18:48 作者: 魔鬼在游行 時(shí)間: 2025-3-29 02:37 作者: Digest 時(shí)間: 2025-3-29 05:39 作者: BIAS 時(shí)間: 2025-3-29 07:13
,Straightforward Layer-Wise Pruning for?More Efficient Visual Adaptation,dimensional space obtained through ch1tspsSNE, SLS facilitates informed pruning decisions. Our study reveals that layer-wise pruning, with a focus on storing pruning indices, addresses storage volume concerns. Notably, mainstream Layer-wise pruning methods may not be suitable for assessing layer imp作者: Scintillations 時(shí)間: 2025-3-29 13:31 作者: 睨視 時(shí)間: 2025-3-29 16:50 作者: Entirety 時(shí)間: 2025-3-29 23:32
,Domain Shifting: A Generalized Solution for?Heterogeneous Cross-Modality Person Re-Identification,lities. Further, a domain alignment loss is developed to alleviate the cross-modality discrepancies by aligning the patterns across modalities. In addition, a domain distillation loss is designed to distill identity-invariant knowledge by learning the distribution of different modalities. Extensive 作者: 分貝 時(shí)間: 2025-3-30 03:02
,Self-Supervised Video Desmoking for?Laparoscopic Surgery,zation term are presented to avoid trivial solutions. In addition, we construct a real surgery video dataset for desmoking, which covers a variety of smoky scenes. Extensive experiments on the dataset show that our SelfSVD can remove smoke more effectively and efficiently while recovering more photo作者: Toxoid-Vaccines 時(shí)間: 2025-3-30 08:05
,Removing Rows and?Columns of?Tokens in?Vision Transformer Enables Faster Dense Prediction Without Rsed fusion method with faster speed and demonstrates higher potential in terms of robustness. Our method was applied to Segmenter, MaskDINO and SWAG, exhibiting promising performance on four tasks, including semantic segmentation, instance segmentation, panoptic segmentation, and image classificatio作者: 赦免 時(shí)間: 2025-3-30 11:20
Allgemeine Immunologie und Immunpathologieng additional generic features free of the source model’s CDS bias. This provides a “second-opinion” regarding which nearest neighbors are more suitable for adaptation. We evaluate our method?using various types of features, datasets and tasks, outperforming previous methods in SFDA under CDS. Our c作者: misshapen 時(shí)間: 2025-3-30 12:54
https://doi.org/10.1007/978-3-642-75228-5dividual features and a try-on module refining the attire?and generating missing parts integrated with a mask-aware post-processing technique ensuring the integrity of the individual’s identity. It demonstrates impressive results, surpassing?the state-of-the-art in speed by nearly 20 times during in作者: 易于 時(shí)間: 2025-3-30 18:47 作者: 他去就結(jié)束 時(shí)間: 2025-3-30 22:58 作者: 供過于求 時(shí)間: 2025-3-31 01:40 作者: 中古 時(shí)間: 2025-3-31 05:05
https://doi.org/10.1007/978-3-642-91030-2 fusion ability while still enjoying efficient inference latency and memory consumption during inference. Extensive experiments on the nuScenes benchmark demonstrate its effectiveness, achieving a new state-of-the-art performance of 57.4. mAP and 65.1. NDS on the test set. The real-time version (25.作者: CHIP 時(shí)間: 2025-3-31 10:56
S?tze und Texte verstehen und produzierenis disentangled from the shape latent space. The proposed deformation representation, which works by predicting skinning weights and rigid transformations for multiple parts, also has advantages over the deformation modules of existing 4D representations in understanding the structure of shapes. In 作者: Cantankerous 時(shí)間: 2025-3-31 16:14
Volition und kognitive Kontrollerial inputs, significantly enhancing its overall robustness. By integrating these methodologies, DGAD significantly improves upon the accuracy of clean data and fortifies the model’s defenses against sophisticated adversarial threats. Our experimental validation on CIFAR10, CIFAR100, and Tiny ImageN作者: 有組織 時(shí)間: 2025-3-31 18:49
Multisensorische Informationsverarbeitungrmation. The two volumes are finally fused to fully represent motion and appearance. This divide-and-conquer strategy leads to more robust tracking through occlusions and deformations and meanwhile obtains decomposed appearances. We conduct evaluations on the TAP-Vid benchmark. The results demonstra作者: PHON 時(shí)間: 2025-3-31 22:06
Kategorisierung und Wissenserwerbdimensional space obtained through ch1tspsSNE, SLS facilitates informed pruning decisions. Our study reveals that layer-wise pruning, with a focus on storing pruning indices, addresses storage volume concerns. Notably, mainstream Layer-wise pruning methods may not be suitable for assessing layer imp作者: disparage 時(shí)間: 2025-4-1 02:13
