离开可分裂
发表于 2025-3-28 16:51:05
http://reply.papertrans.cn/24/2342/234186/234186_41.png
Frequency-Range
发表于 2025-3-28 19:46:04
http://reply.papertrans.cn/24/2342/234186/234186_42.png
袋鼠
发表于 2025-3-29 01:14:23
Shift-Net: Image Inpainting via Deep Feature Rearrangementature in missing region can be used to guide the shift of encoder feature in known region. An end-to-end learning algorithm is further developed to train the Shift-Net. Experiments on the Paris StreetView and Places datasets demonstrate the efficiency and effectiveness of our Shift-Net in producing
并置
发表于 2025-3-29 03:42:22
http://reply.papertrans.cn/24/2342/234186/234186_44.png
虚弱的神经
发表于 2025-3-29 09:31:18
Modular Generative Adversarial Networksains, and then combined to construct specific GAN networks at test time, according to the specific image translation task. This leads to ModularGAN’s superior flexibility of generating (or translating to) an image in any desired domain. Experimental results demonstrate that our model not only presen
outrage
发表于 2025-3-29 12:03:50
http://reply.papertrans.cn/24/2342/234186/234186_46.png
Dendritic-Cells
发表于 2025-3-29 15:37:51
Single Image Intrinsic Decomposition Without a Single Intrinsic Imageam module that performs intrinsic decomposition on a single input image. We demonstrate the effectiveness of our framework through extensive experimental study on both synthetic and real-world datasets, showing superior performance over previous approaches in both single-image and multi-image settin
微粒
发表于 2025-3-29 22:40:15
PersonLab: Person Pose Estimation and Instance Segmentation with a Bottom-Up, Part-Based, Geometric stem achieves COCO test-dev keypoint average precision of 0.665 using single-scale inference and 0.687 using multi-scale inference, significantly outperforming all previous bottom-up pose estimation systems. We are also the first bottom-up method to report competitive results for the person class in
越自我
发表于 2025-3-30 01:00:58
http://reply.papertrans.cn/24/2342/234186/234186_49.png
Neutropenia
发表于 2025-3-30 04:29:05
The dynamic context of employee relationsature in missing region can be used to guide the shift of encoder feature in known region. An end-to-end learning algorithm is further developed to train the Shift-Net. Experiments on the Paris StreetView and Places datasets demonstrate the efficiency and effectiveness of our Shift-Net in producing