作者: 北極熊 時間: 2025-3-21 22:57 作者: Ballerina 時間: 2025-3-22 01:20 作者: Creatinine-Test 時間: 2025-3-22 04:59 作者: reject 時間: 2025-3-22 08:50 作者: 伙伴 時間: 2025-3-22 14:56 作者: 伙伴 時間: 2025-3-22 18:02 作者: Collision 時間: 2025-3-23 01:13
Alternativen zur Erwerbsarbeit?s suffer from inconsistent 3D geometry or mediocre rendering quality due to improper representations. We take a step towards resolving these shortcomings by utilizing the recent state-of-the-art 3D explicit representation, Gaussian Splatting, and an unconditional diffusion model. This model learns t作者: 合并 時間: 2025-3-23 01:58
,Dienstleistungsvertrag für Wohnmakler,rios, is hampered by their inherently slow generation speed. The slow generation stems from the necessity of multi-step network inference. While some certain predictions benefit from the full computation of the model in each sampling iteration, not every iteration requires the same amount of computa作者: Grandstand 時間: 2025-3-23 08:15
The epiCS? Skin Irritation Test (SIT) Methodoblem facing FL is that the model utility drops significantly once the data distribution gets heterogeneous, or non-i.i.d, among clients. A promising solution is to personalize models for each client, e.g., keeping some layers locally without aggregation, which is thus called personalized FL. Howeve作者: craven 時間: 2025-3-23 11:14
Helena Kandarova,Manfred Liebschrowing attention in recent years, where existing approaches focus on self-training that usually includes pseudo-labeling techniques. In this paper, we introduce a novel noise-learning approach tailored to address noise distribution in domain adaptation settings and learn to .. More specifically, we 作者: 多節(jié) 時間: 2025-3-23 15:19
https://doi.org/10.1007/978-3-319-50353-0deling. However, its applications in 3D medical imaging, such as CT and MRI, which are crucial for critical care, remain unexplored. In this paper, we introduce .. GenerateCT incorporates a text encoder and three key components: a novel causal vision transformer for encoding 3D CT volumes, a text-im作者: 滔滔不絕的人 時間: 2025-3-23 18:58
Alexander Minnaert,Piet J. Janssenthis task? Prior works often fail by making global changes to the image, inserting objects in unrealistic spatial locations, and generating inaccurate lighting details. We observe that while state-of-the-art models perform poorly on object insertion, they can remove objects and erase the background 作者: 項目 時間: 2025-3-23 23:01 作者: 假設(shè) 時間: 2025-3-24 04:24 作者: 提升 時間: 2025-3-24 07:57 作者: 有法律效應(yīng) 時間: 2025-3-24 13:37 作者: 熱心助人 時間: 2025-3-24 15:39
Bipransh Kumar Tiwary,Kiran Pradhanrence process of pretrained diffusion models to achieve zero-shot capabilities. An example is the generation of panorama images, which has been tackled in recent works by combining independent diffusion paths over overlapping latent features, which is referred to as ., obtaining perceptually aligned作者: indoctrinate 時間: 2025-3-24 21:22
Rejuan Islam,Anirban Pandey,Tilak Sahaaddress these challenges, we propose DynMF, a compact and efficient representation that decomposes a dynamic scene into a few neural trajectories. We argue that the per-point motions of a dynamic scene can be decomposed into a small set of explicit or learned trajectories. Our carefully designed neu作者: EXALT 時間: 2025-3-25 00:49
Alternatives to Neoliberal Globalization movements and have a variety of appearance details (e.g., fur, spots, tails). We develop an approach that links the video frames via a 4D solution that jointly solves for animal’s pose variation, and its appearance (in a canonical pose). To this end, we significantly improve the quality of template作者: 屈尊 時間: 2025-3-25 05:16
Michael A. Mullen,John R. Pedersen However, the growth is not attributed solely to models and benchmarks. Universally accepted evaluation metrics also play an important role in advancing the field. While there are many metrics available to evaluate audio and visual content separately, there is a lack of metrics that offer a quantita作者: 火海 時間: 2025-3-25 07:45
David Moore,Jeffrey C. Lord,Susan M. Smithhe format of low-resolution radar point clouds and usually under an open-space single-room setting. In this paper, we scale up indoor radar data collection using multi-view high-resolution radar heatmap in a multi-day, multi-room, and multi-subject setting, with an emphasis on the diversity of envir作者: 嫌惡 時間: 2025-3-25 14:08 作者: 學(xué)術(shù)討論會 時間: 2025-3-25 15:55 作者: 伸展 時間: 2025-3-25 20:57 作者: molest 時間: 2025-3-26 00:13
Luis Alonso-Ovalle,Paula Menéndez-Benitoc segmentation failed and show how recently proposed robust . backbones can be used to obtain adversarially robust semantic segmentation models with up to six times less training time for . and the more challenging .. The associated code and robust models are available at ..作者: Tdd526 時間: 2025-3-26 08:15
,De-confusing Pseudo-labels in?Source-Free Domain Adaptation,fectiveness of our approach when combined with several source-free domain adaptation methods: SHOT, SHOT++, and AaD. We obtain state-of-the-art results on three domain adaptation datasets: VisDA, DomainNet, and OfficeHome.作者: mechanical 時間: 2025-3-26 11:48 作者: 高射炮 時間: 2025-3-26 12:37 作者: 雪白 時間: 2025-3-26 17:16
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: 商談 時間: 2025-3-26 23:04 作者: Commentary 時間: 2025-3-27 04:42
,Evaluating the?Adversarial Robustness of?Semantic Segmentation: Trying Harder Pays Off,than previously reported. We also demonstrate a size-bias: small objects are often more easily attacked, even if the large objects are robust, a phenomenon not revealed by current evaluation metrics. Our results also demonstrate?that a diverse set of strong attacks is necessary, because different mo作者: APO 時間: 2025-3-27 05:17
,SKYSCENES: A Synthetic Dataset for?Aerial Scene Understanding,point conditions (height and pitch), weather and time of day, and (4) incorporating additional sensor modalities (depth) can improve aerial scene understanding. Our dataset and associated generation code are publicly available at: 作者: organic-matrix 時間: 2025-3-27 11:19
Large-Scale Multi-hypotheses Cell Tracking Using Ultrametric Contours Maps,a faster integer linear programming formulation, and the framework is flexible, supporting segmentations from individual off-the-shelf cell segmentation models or their combination as an ensemble. The code is available as supplementary material.作者: 遠(yuǎn)足 時間: 2025-3-27 14:32 作者: 外貌 時間: 2025-3-27 20:06 作者: Minutes 時間: 2025-3-27 23:29 作者: 不連貫 時間: 2025-3-28 02:52 作者: endarterectomy 時間: 2025-3-28 06:20
,EraseDraw: Learning to?Insert Objects by?Erasing Them from?Images,r model achieves state-of-the-art results in object insertion, particularly for in-the-wild images. We show compelling results on diverse insertion prompts and images across various domains. In addition, we automate iterative insertion by combining our insertion model with beam search guided by CLIP作者: inquisitive 時間: 2025-3-28 14:25
,SuperFedNAS: Cost-Efficient Federated Neural Architecture Search for?On-device Inference,tedly for each case. SuperFedNAS addresses these challenges by decoupling the training and search in federated NAS. SuperFedNAS co-trains a large number of diverse DNN architectures contained inside one supernet in the FL setting. Post-training, clients perform NAS locally to find specialized DNNs b作者: 招致 時間: 2025-3-28 16:26
,Contrastive Region Guidance: Improving Grounding in?Vision-Language Models Without Training,VL tasks: When region annotations are provided, CRG increases absolute accuracy by up to . on ViP-Bench, a collection of six diverse region-based tasks such as recognition, math, and object relationship reasoning. We also show CRG’s applicability to spatial reasoning, with . improvement on What’sUp,作者: Medicare 時間: 2025-3-28 22:20
Keypoint Promptable Re-Identification,ons necessary for prompting. To bridge this gap and foster further research on this topic,?we introduce Occluded PoseTrack-ReID, a novel ReID dataset with keypoints labels, that features strong inter-person occlusions. Furthermore, we release custom keypoint labels for four popular ReID benchmarks. 作者: 不妥協(xié) 時間: 2025-3-29 02:46 作者: 外來 時間: 2025-3-29 05:19 作者: 冷淡周邊 時間: 2025-3-29 11:04
,Animal Avatars: Reconstructing Animatable 3D Animals from?Casual Videos,etric compatibility with the input video frames. On the challenging CoP3D and APTv2 datasets, we demonstrate superior results (both in terms of pose estimates and predicted appearance) over existing template-free (RAC) and template-based approaches (BARC, BITE). Video results and additional informat作者: palpitate 時間: 2025-3-29 11:35 作者: 恭維 時間: 2025-3-29 19:07 作者: 現(xiàn)實 時間: 2025-3-29 22:43 作者: 出處 時間: 2025-3-30 01:40
Alternativen zur Erwerbsarbeit?than previously reported. We also demonstrate a size-bias: small objects are often more easily attacked, even if the large objects are robust, a phenomenon not revealed by current evaluation metrics. Our results also demonstrate?that a diverse set of strong attacks is necessary, because different mo作者: Gum-Disease 時間: 2025-3-30 06:11
Informelle ?konomie in Grossbritannienpoint conditions (height and pitch), weather and time of day, and (4) incorporating additional sensor modalities (depth) can improve aerial scene understanding. Our dataset and associated generation code are publicly available at: 作者: Monocle 時間: 2025-3-30 10:20
“Kosten” und Nutzen von Selbsthilfegruppena faster integer linear programming formulation, and the framework is flexible, supporting segmentations from individual off-the-shelf cell segmentation models or their combination as an ensemble. The code is available as supplementary material.作者: 惡心 時間: 2025-3-30 14:15 作者: Parameter 時間: 2025-3-30 17:52
,Dienstleistungsvertrag für Wohnmakler,cally allocates computation resources in each sampling step to improve the generation efficiency of diffusion models. To assess the effects of changes in computational effort on image quality, we present a timestep-aware uncertainty estimation module (UEM). Integrated at each intermediate layer, the作者: muster 時間: 2025-3-30 20:49 作者: Polydipsia 時間: 2025-3-31 02:01 作者: 連詞 時間: 2025-3-31 05:57
Alexander Minnaert,Piet J. Janssenr model achieves state-of-the-art results in object insertion, particularly for in-the-wild images. We show compelling results on diverse insertion prompts and images across various domains. In addition, we automate iterative insertion by combining our insertion model with beam search guided by CLIP作者: Conjuction 時間: 2025-3-31 09:22
Alexander Minnaert,Piet J. Janssentedly for each case. SuperFedNAS addresses these challenges by decoupling the training and search in federated NAS. SuperFedNAS co-trains a large number of diverse DNN architectures contained inside one supernet in the FL setting. Post-training, clients perform NAS locally to find specialized DNNs b作者: 旁觀者 時間: 2025-3-31 14:35
Nilotpal Borah,Abhijit Gogoi,Jiban SaikiaVL tasks: When region annotations are provided, CRG increases absolute accuracy by up to . on ViP-Bench, a collection of six diverse region-based tasks such as recognition, math, and object relationship reasoning. We also show CRG’s applicability to spatial reasoning, with . improvement on What’sUp,作者: Wernickes-area 時間: 2025-3-31 19:27
Nilotpal Borah,Abhijit Gogoi,Jiban Saikiaons necessary for prompting. To bridge this gap and foster further research on this topic,?we introduce Occluded PoseTrack-ReID, a novel ReID dataset with keypoints labels, that features strong inter-person occlusions. Furthermore, we release custom keypoint labels for four popular ReID benchmarks. 作者: 減弱不好 時間: 2025-3-31 22:06
Bipransh Kumar Tiwary,Kiran Pradhanand cross-attention to operate on the aggregated latent space. Extensive quantitative and qualitative experimental analysis, together with a user study, demonstrate that our method maintains compatibility with the input prompt and visual quality of the generated images while increasing their semanti作者: CROW 時間: 2025-4-1 02:08
Rejuan Islam,Anirban Pandey,Tilak Sahaients that enforce the per-point sharing of basis trajectories. By carefully applying a sparsity loss to the motion coefficients, we are able to disentangle the motions that comprise the scene, independently control them, and generate novel motion combinations that have never been seen before. We ca作者: Mirage 時間: 2025-4-1 07:43 作者: 注意 時間: 2025-4-1 12:18 作者: Generosity 時間: 2025-4-1 15:51 作者: PANG 時間: 2025-4-1 18:30
Alternatives to State-Socialism in Britainining, the weights perturbations are maximized on simulated out-of-distribution (OOD) data to heighten the challenge of model theft, while being minimized on in-distribution (ID) training data to preserve model utility. Additionally, we formulate an attack-aware defensive training objective function作者: 車床 時間: 2025-4-2 00:32
,Evaluating the?Adversarial Robustness of?Semantic Segmentation: Trying Harder Pays Off,lity, we need reliable methods that can find such adversarial perturbations. For image classification models, evaluation methodologies have emerged that have stood the test of time. However, we argue that in the area of semantic segmentation, a good approximation of the sensitivity to adversarial pe作者: 頑固 時間: 2025-4-2 05:33
,SKYSCENES: A Synthetic Dataset for?Aerial Scene Understanding,. Due to inherent challenges in obtaining such images in controlled real-world settings, we present ., a synthetic dataset of densely annotated aerial images captured from Unmanned Aerial Vehicle (UAV) perspectives. We carefully curate . images from . to comprehensively capture diversity across layo作者: 箴言 時間: 2025-4-2 08:40
Large-Scale Multi-hypotheses Cell Tracking Using Ultrametric Contours Maps,cking cells across large microscopy datasets on two fronts: (i) It can solve problems containing millions of segmentation instances in terabyte-scale 3D+t datasets; (ii) It achieves competitive results with or without deep learning, bypassing the requirement of 3D annotated data, that is scarce in t
