使出神
发表于 2025-3-28 14:49:12
,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.
分发
发表于 2025-3-28 18:48:50
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魔鬼在游行
发表于 2025-3-29 02:37:57
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Digest
发表于 2025-3-29 05:39:01
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BIAS
发表于 2025-3-29 07:13:16
,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
Scintillations
发表于 2025-3-29 13:31:47
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睨视
发表于 2025-3-29 16:50:22
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Entirety
发表于 2025-3-29 23:32:17
,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
分贝
发表于 2025-3-30 03:02:19
,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
Toxoid-Vaccines
发表于 2025-3-30 08:05:30
,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