backdrop
发表于 2025-3-25 03:22:55
http://reply.papertrans.cn/25/2424/242303/242303_21.png
遍及
发表于 2025-3-25 10:13:55
,Distilling Knowledge from Large-Scale Image Models for Object Detection, exhibits sparse query locations, thereby facilitating the distillation process. (2) Considering that large-scale detectors are mainly based on DETRs, we propose a Query Distillation (QD) method specifically tailored for DETRs. The QD performs knowledge distillation by leveraging the spatial positio
破布
发表于 2025-3-25 14:37:23
,Embracing Events and Frames with Hierarchical Feature Refinement Network for Object Detection,ted extensive experiments on two benchmarks: the low-resolution PKU-DDD17-Car dataset and the high-resolution DSEC dataset. Experimental results show that our method surpasses the state-of-the-art by an impressive margin of . on the DSEC dataset. Besides, our method exhibits significantly better rob
Offset
发表于 2025-3-25 16:57:17
http://reply.papertrans.cn/25/2424/242303/242303_24.png
强制性
发表于 2025-3-25 20:53:49
http://reply.papertrans.cn/25/2424/242303/242303_25.png
corporate
发表于 2025-3-26 01:11:34
http://reply.papertrans.cn/25/2424/242303/242303_26.png
facetious
发表于 2025-3-26 05:51:19
http://reply.papertrans.cn/25/2424/242303/242303_27.png
SAGE
发表于 2025-3-26 09:37:57
,Identity-Consistent Diffusion Network for Grading Knee Osteoarthritis Progression in Radiographic Im generation-guided progression prediction module are introduced. Compared to conventional image-to-image generative models, identity priors regularize and guide the diffusion to focus more on the clinical nuances of the prognosis based on a contrastive learning strategy. The progression prediction
执
发表于 2025-3-26 14:16:42
http://reply.papertrans.cn/25/2424/242303/242303_29.png
reserve
发表于 2025-3-26 18:16:26
http://reply.papertrans.cn/25/2424/242303/242303_30.png