ATOPY
发表于 2025-3-23 13:33:03
,ByteEdit: Boost, Comply and Accelerate Generative Image Editing,npainting tasks. Despite these strides, the field grapples with inherent challenges, including: i) inferior quality; ii) poor consistency; iii) insufficient instrcution adherence; iv) suboptimal generation efficiency. To address these obstacles, we present ., an innovative feedback learning framewor
虚弱的神经
发表于 2025-3-23 16:05:30
,ProDepth: Boosting Self-supervised Multi-frame Monocular Depth with Probabilistic Fusion,scene. However, the presence of moving objects in dynamic scenes introduces inevitable inconsistencies, causing misaligned multi-frame feature matching and misleading self-supervision during training. In this paper, we propose a novel framework called ProDepth, which effectively addresses the mismat
职业拳击手
发表于 2025-3-23 19:05:05
http://reply.papertrans.cn/25/2424/242314/242314_13.png
天文台
发表于 2025-3-23 23:26:23
,Accelerating Image Super-Resolution Networks with Pixel-Level Classification,or DNN-based SISR, decomposing images into overlapping patches is typically necessary due to computational constraints. In such patch-decomposing scheme, one can allocate computational resources differently based on each patch’s difficulty to further improve efficiency while maintaining SR performan
赏心悦目
发表于 2025-3-24 04:44:21
http://reply.papertrans.cn/25/2424/242314/242314_15.png
让你明白
发表于 2025-3-24 07:50:28
http://reply.papertrans.cn/25/2424/242314/242314_16.png
SOBER
发表于 2025-3-24 13:41:25
,Click-Gaussian: Interactive Segmentation to Any 3D Gaussians,y of 3D Gaussian Splatting. However, the current methods suffer from time-consuming post-processing to deal with noisy segmentation output. Also, they struggle to provide detailed segmentation, which is important for fine-grained manipulation of 3D scenes. In this study, we propose Click-Gaussian, w
infinite
发表于 2025-3-24 15:16:04
http://reply.papertrans.cn/25/2424/242314/242314_18.png
CLAMP
发表于 2025-3-24 21:24:19
,DySeT: A Dynamic Masked Self-distillation Approach for Robust Trajectory Prediction,address this is via self-supervised pre-training through masked trajectory prediction. However, the existing models rely on uniform random sampling of tokens, which is sub-optimal because it implies that all components of driving scenes are equally informative. In this paper, to enable more robust r
comely
发表于 2025-3-25 00:48:26
http://reply.papertrans.cn/25/2424/242314/242314_20.png