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

繁重

,Enhancing Optimization Robustness in 1-Bit Neural Networks Through Stochastic Sign Descent,ligning noisy floating-point gradients with binary parameters. To address this, we introduce Diode, a groundbreaking optimizer designed explicitly for BNNs that bridges this gap by utilizing the gradient’s sign information in a unique, latent-weight-free approach. By focusing on the gradient sign’s

向外才掩饰

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/242327.jpg

mydriatic

愚笨

矛盾

啪心儿跳动

1.5.1.7.3 Cold working, plastic deformation,er-based methods do not leverage the geometric priors of the triplane component in their architecture, often leading to sub-optimal quality given the limited size of 3D data and slow training. In this work, we present the Convolutional Reconstruction Model (CRM), a high-fidelity feed-forward single