作者: 只有 時間: 2025-3-22 00:11 作者: PANT 時間: 2025-3-22 03:29
https://doi.org/10.1007/978-3-031-72784-9artificial intelligence; computer networks; computer systems; computer vision; education; Human-Computer 作者: crease 時間: 2025-3-22 07:03
978-3-031-72783-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl作者: 輪流 時間: 2025-3-22 10:59 作者: GROVE 時間: 2025-3-22 15:38
General Introduction by Guerino Mazzolatruggle with problems of low overlap, thus limiting their practical usage. In this paper, we propose ML-SemReg, a plug-and-play point cloud registration framework that fully exploits semantic information. Our key insight is that mismatches can be categorized into two types, i.e., inter- and intra-cl作者: GROVE 時間: 2025-3-22 18:22
General Introduction by Guerino Mazzolaoaches heavily rely on laborious annotations and present hampered generalization ability due to the limited diversity of 3D pose datasets. To address these challenges, we propose a unified framework that leverages mask as supervision for unsupervised 3D pose estimation. With general unsupervised seg作者: 使困惑 時間: 2025-3-22 21:23 作者: CT-angiography 時間: 2025-3-23 03:15 作者: 開始沒有 時間: 2025-3-23 09:16 作者: 不可比擬 時間: 2025-3-23 12:36 作者: Matrimony 時間: 2025-3-23 15:38
https://doi.org/10.1007/978-90-481-9316-5e tasks, existing methodologies often struggle to generate high-caliber results. We begin by examining the inherent limitations in previous diffusion priors. We identify a divergence between the diffusion priors and the training procedures of diffusion models that substantially impairs the quality o作者: Banister 時間: 2025-3-23 20:38
Zoochory: The Dispersal Of Plants By Animalsintra-frame consistency. Existing methods fall short in either generation quality or flexibility. We introduce MOTIA (.astering Video .utpainting .hrough .nput-Specific .daptation), a diffusion-based pipeline that leverages both the intrinsic data-specific patterns of the source video and the image/作者: 粉筆 時間: 2025-3-24 02:15
Serge Yan Landau,Giovanni Mollen. Multi-camera systems are commonly used as the image capture setup in NeRF-based multi-view tasks such as dynamic scene acquisition or realistic avatar animation. However, a critical issue that has often been overlooked in this setup is the evident differences in color responses among multiple cam作者: V洗浴 時間: 2025-3-24 05:43
Zoochory: The Dispersal Of Plants By Animals3D scene. However, a considerable gap exists between existing methods and such a unified model, due to the independent application of representation and insufficient exploration of 3D multi-task training. In this paper, we introduce., a unified model capable of using .romptable .ueries to tackle a w作者: 大約冬季 時間: 2025-3-24 08:19
Zoochory: The Dispersal Of Plants By Animals performance. Breaking away from traditional practices that need a multitude of fine-tuned models for averaging, our approach employs significantly fewer models to achieve final weights yet yield superior accuracy. Drawing from key insights in the weight space of fine-tuned weights, we uncover a str作者: 仲裁者 時間: 2025-3-24 14:09
Intestinal Spirochetes of Termiteseproduce their high-resolution (HR) counterparts with high quality. Recently, the diffusion models have shown compelling performance in generating realistic details for image restoration tasks. However, the diffusion process has randomness, making it hard to control the contents of restored images. 作者: Substance 時間: 2025-3-24 18:51 作者: PHAG 時間: 2025-3-24 19:09 作者: 襲擊 時間: 2025-3-25 00:57
How Can Spiders Grow Despite an Exoskeleton?tains subtle errors and imperfections stemming from its annotation procedure. With the advent of high-performing models, we ask whether these errors of COCO are hindering its utility in reliably benchmarking further progress. In search for an answer, we inspect thousands of masks from COCO (2017 ver作者: 罐里有戒指 時間: 2025-3-25 05:43
Convergence of Random Variablesance for wildlife conservation, ecological research, and environmental monitoring. Existing wildlife ReID methods are predominantly tailored to specific species, exhibiting limited applicability. Although some approaches leverage extensively studied person ReID techniques, they struggle to address t作者: Foreknowledge 時間: 2025-3-25 10:42
Models, Statistical Inference and Learninglevel segmentation remains underexplored due to complex boundaries and scarce annotated data. To address this, we propose a novel .eakly-supervised .art .egmentation (.) setting and an approach called ., built on the large-scale pre-trained vision foundation model, Segment Anything Model (SAM). WPS-作者: 清唱劇 時間: 2025-3-25 14:30 作者: agglomerate 時間: 2025-3-25 17:21 作者: PHONE 時間: 2025-3-25 20:00 作者: 笨拙的我 時間: 2025-3-26 01:38 作者: CANON 時間: 2025-3-26 04:24 作者: Grandstand 時間: 2025-3-26 11:35 作者: 教義 時間: 2025-3-26 15:43 作者: 針葉樹 時間: 2025-3-26 18:30 作者: 震驚 時間: 2025-3-27 00:21
General Introduction by Guerino Mazzolae data and provides ready-to-use estimation results. Comprehensive experiments demonstrate our state-of-the-art pose estimation performance on Human3.6M and MPI-INF-3DHP datasets. Further experiments on in-the-wild datasets also illustrate the capability to access more data to boost our model. Code will be available at ..作者: DAUNT 時間: 2025-3-27 02:03
Clinical Assessment of Mucociliary Disorders a variational autoencoder, and leverage a diffusion model to enhance expressivity. Additionally, we instruct the model to preserve 3D structural fidelity by devising a range-guided discriminator. Experimental results on KITTI-360 and nuScenes datasets demonstrate both the robust expressiveness and fast speed of our LiDAR point cloud generation.作者: 發(fā)微光 時間: 2025-3-27 06:54
Models, Statistical Inference and Learningting the rich knowledge embedded in pre-trained foundation models, WPS-SAM outperforms other segmentation models trained with pixel-level strong annotations. Specifically, WPS-SAM achieves 68.93% mIOU and 79.53% mACC on the PartImageNet dataset, surpassing state-of-the-art fully supervised methods by approximately 4% in terms of mIOU.作者: 開頭 時間: 2025-3-27 12:44
,ComFusion: Enhancing Personalized Generation by?Instance-Scene Compositing and?Fusion,s coarse-generated images to ensure alignment with both the instance images and scene texts, thereby achieving a delicate balance between capturing the subject’s essence and maintaining scene fidelity. Extensive evaluations of ComFusion against various baselines in T2I personalization have demonstrated its qualitative and quantitative superiority.作者: 一個姐姐 時間: 2025-3-27 15:03
,Mask as?Supervision: Leveraging Unified Mask Information for?Unsupervised 3D Pose Estimation,e data and provides ready-to-use estimation results. Comprehensive experiments demonstrate our state-of-the-art pose estimation performance on Human3.6M and MPI-INF-3DHP datasets. Further experiments on in-the-wild datasets also illustrate the capability to access more data to boost our model. Code will be available at ..作者: 手段 時間: 2025-3-27 19:44 作者: EVADE 時間: 2025-3-27 23:49
,WPS-SAM: Towards Weakly-Supervised Part Segmentation with?Foundation Models,ting the rich knowledge embedded in pre-trained foundation models, WPS-SAM outperforms other segmentation models trained with pixel-level strong annotations. Specifically, WPS-SAM achieves 68.93% mIOU and 79.53% mACC on the PartImageNet dataset, surpassing state-of-the-art fully supervised methods by approximately 4% in terms of mIOU.作者: Dedication 時間: 2025-3-28 03:03 作者: gerontocracy 時間: 2025-3-28 07:40
,MoVideo: Motion-Aware Video Generation with?Diffusion Model, space by another spatio-temporal diffusion model under the guidance of depth, optical flow-based warped latent video and the calculated occlusion mask. Lastly, we use optical flows again to align and refine different frames for better video decoding from the latent space to the pixel space. In expe作者: 無動于衷 時間: 2025-3-28 12:08
,SHERL: Synthesizing High Accuracy and?Efficient Memory for?Resource-Limited Transfer Learning,esses. In the early route, intermediate outputs are consolidated via an anti-redundancy operation, enhancing their compatibility for subsequent interactions; thereby in the late route, utilizing minimal late pre-trained layers could alleviate the peak demand on memory overhead and regulate these fai作者: 相符 時間: 2025-3-28 16:58 作者: 全部 時間: 2025-3-28 20:16
,Learn to?Optimize Denoising Scores: A Unified and?Improved Diffusion Prior for?3D Generation,lishing new state-of-the-art in the realm of text-to-3D generation. Additionally, our framework yields insightful contributions to the understanding of recent score distillation methods, such as the VSD loss and CSD loss. Code: ..作者: 名字的誤用 時間: 2025-3-28 23:50 作者: 兇兆 時間: 2025-3-29 06:15 作者: CONE 時間: 2025-3-29 09:09 作者: 容易做 時間: 2025-3-29 13:23 作者: slow-wave-sleep 時間: 2025-3-29 18:24 作者: UNT 時間: 2025-3-29 22:41
PoseCrafter: One-Shot Personalized Video Synthesis Following Flexible Pose Control,ter achieves superior results to baselines pre-trained on a vast collection of videos under 8 commonly used metrics. Besides, PoseCrafter can follow poses from different individuals or artificial edits and simultaneously retain the human identity in an open-domain training video. Our project page is作者: GLIB 時間: 2025-3-30 02:31 作者: Eeg332 時間: 2025-3-30 07:58
,Adaptive High-Frequency Transformer for?Diverse Wildlife Re-identification,mitigate the inevitable high-frequency interference in the wilderness environment, we introduce an object-aware high-frequency selection strategy to adaptively capture more valuable high-frequency components. Notably, we unify the experimental settings of multiple wildlife datasets for ReID, achievi作者: 遭遇 時間: 2025-3-30 10:40 作者: 歸功于 時間: 2025-3-30 14:11 作者: Terminal 時間: 2025-3-30 20:12 作者: MELD 時間: 2025-3-30 23:53
https://doi.org/10.1007/978-3-319-47334-5esses. In the early route, intermediate outputs are consolidated via an anti-redundancy operation, enhancing their compatibility for subsequent interactions; thereby in the late route, utilizing minimal late pre-trained layers could alleviate the peak demand on memory overhead and regulate these fai作者: aspect 時間: 2025-3-31 04:07
Tu?ba Ko?ak,Aytu? Altunda?,Thomas Hummele adaptation to fail in Mono 3Det. To handle this problem, we propose a novel .cular .est-.ime .daptation (.) method, based on two new strategies. 1) Reliability-driven adaptation: we empirically find that . and the optimization of high-score objects can .. Thus, we devise a self-adaptive strategy t作者: Statins 時間: 2025-3-31 06:35 作者: 平息 時間: 2025-3-31 10:55 作者: FICE 時間: 2025-3-31 14:05
Serge Yan Landau,Giovanni Molleenabling the unified color NeRF reconstruction. Besides the view-independent color correction module for external differences, we predict a view-dependent function to minimize the color residual (including, .., specular and shading) to eliminate the impact of inherent attributes. We further describe作者: 尖牙 時間: 2025-3-31 17:30
Zoochory: The Dispersal Of Plants By Animals support multi-task training. Tested across ten diverse 3D-VL datasets, . demonstrates impressive performance on these tasks, setting new records on most benchmarks. Particularly, . improves the state-of-the-art on ScanNet200 by 4.9% (AP25), ScanRefer by 5.4% (acc@0.5), Multi3DRefer by 11.7% (F1@0.5作者: 哪有黃油 時間: 2025-3-31 23:22
Zoochory: The Dispersal Of Plants By Animalsing a minimal number of models to draw a more optimized-averaged model. We demonstrate the efficacy of Model Stock with fine-tuned models based upon pre-trained CLIP architectures, achieving remarkable performance on both ID and OOD tasks on the standard benchmarks, all while barely bringing extra c作者: Bph773 時間: 2025-4-1 03:20
Intestinal Spirochetes of Termitesg path with a motion-guided loss, ensuring that the generated HR video maintains a coherent and continuous visual flow. To further mitigate the discontinuity of generated details, we insert temporal module to the decoder and fine-tune it with an innovative sequence-oriented loss. The proposed motion作者: Compass 時間: 2025-4-1 06:50
,Here’s How Freudenthal Saw It,ter achieves superior results to baselines pre-trained on a vast collection of videos under 8 commonly used metrics. Besides, PoseCrafter can follow poses from different individuals or artificial edits and simultaneously retain the human identity in an open-domain training video. Our project page is作者: 油氈 時間: 2025-4-1 12:52
