Titlebook: Computer Vision – ECCV 2024; 18th European Confer Aleš Leonardis,Elisa Ricci,Gül Varol Conference proceedings 2025 The Editor(s) (if applic

conceal

,Taming Lookup Tables for Efficient Image Retouching,n. We observe that the pointwise network structure exhibits robust scalability, upkeeping the performance even with a heavily downsampled . input image. These enable ICELUT, the . purely LUT-based image enhancer, to reach an unprecedented speed of 0.4 ms on GPU and 7 ms on CPU, at least one order fa

emission

,DualDn: Dual-Domain Denoising via Differentiable ISP,ts to sensor-specific noise as well as spatially varying noise levels, while the sRGB domain denoising adapts to ISP variations and removes residual noise amplified by the ISP. Both denoising networks are connected with a differentiable ISP, which is trained end-to-end and discarded during the infer

Longitude

玷污

阴谋小团体

ingestion

使成核

,Cross-Domain Few-Shot Object Detection via Enhanced Open-Set Object Detector,proposed measures: style, ICV, and IB. Consequently, we propose several novel modules to address these issues. First, the learnable instance features align initial fixed instances with target categories, enhancing feature distinctiveness. Second, the instance reweighting module assigns higher import

coltish

,NICP: Neural ICP for 3D Human Registration at Scale,izes and scales across thousands of shapes and more than ten different data sources. Our essential contribution is NICP, an ICP-style self-supervised task tailored to neural fields. NICP takes a few seconds, is self-supervised, and works out of the box on pre-trained neural fields. NSR combines NICP

stratum-corneum

啜泣