sparse 发表于 2025-3-26 23:39:44
COG: COnsistent Data AuGmentation for Object Perceptionow that our method COG’s performance is superior to its competitor on detection and instance segmentation tasks. In addition, the results manifest the robustness of COG when faced with hyper-parameter variations, etc.SPECT 发表于 2025-3-27 02:25:05
http://reply.papertrans.cn/24/2342/234128/234128_32.pngVerify 发表于 2025-3-27 07:15:31
http://reply.papertrans.cn/24/2342/234128/234128_33.png脊椎动物 发表于 2025-3-27 13:23:35
http://reply.papertrans.cn/24/2342/234128/234128_34.png集中营 发表于 2025-3-27 16:01:42
http://reply.papertrans.cn/24/2342/234128/234128_35.png遵循的规范 发表于 2025-3-27 21:49:09
http://reply.papertrans.cn/24/2342/234128/234128_36.png洁净 发表于 2025-3-28 00:41:43
https://doi.org/10.1007/978-3-642-67047-3act from the last convolutional layer and show that kernels identified are symbolic in that they react strongly to sets of similar images that effectively divide output classes into sub-classes with distinct characteristics.Abominate 发表于 2025-3-28 02:38:47
http://reply.papertrans.cn/24/2342/234128/234128_38.png凝视 发表于 2025-3-28 07:51:09
http://reply.papertrans.cn/24/2342/234128/234128_39.pngfaultfinder 发表于 2025-3-28 11:00:41
Adaptive Spotting: Deep Reinforcement Object Search in 3D Point Clouds be searched. This network is successfully trained in an end-to-end manner by integrating a contrastive loss and a reinforcement localization reward. Evaluations on ModelNet40 and Stanford 2D-3D-S datasets demonstrate the superiority of the proposed approach over several state-of-the-art baselines.