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

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,3R-INN: How to?Be Climate Friendly While Consuming/Delivering Videos?,d daily, this contributes significantly to the greenhouse gas (GHG) emission. Therefore, reducing the end-to-end carbon footprint of the video chain, while preserving the quality of experience at the user side, is of high importance. To contribute in an impactful manner, we propose 3R-INN, a single

dainty

MAPLE

Towards Robust Full Low-Bit Quantization of Super Resolution Networks,ss of Super Resolution?(SR) networks to low-bit quantization considering mathematical model?of natural images. Natural images contain partially smooth areas?with edges between them. The number of pixels corresponding to edges?is significantly smaller than the overall number of pixels. As SR?task cou

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BUOY

febrile

,Style-Extracting Diffusion Models for?Semi-supervised Histopathology Segmentation,te these developments, generating images?with unseen characteristics beneficial for downstream tasks has received limited attention. To bridge this gap, we propose Style-Extracting Diffusion Models, featuring two conditioning mechanisms. Specifically, we utilize 1) a style conditioning mechanism?whi

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錫箔紙

,Model Breadcrumbs: Scaling Multi-task Model Merging with?Sparse Masks,s fine-tuning these pre-trained foundation models for specific target tasks, resulting in a rapid spread of models fine-tuned across a diverse array of tasks. This work focuses on the problem of merging multiple fine-tunings of the same foundation model derived from a spectrum of auxiliary tasks. We

Interlocking

FAWN

iHuman: Instant Animatable Digital Humans From Monocular Videos,lass of users and wide-scale applications. In this paper, we present a fast, simple, yet effective method for creating animatable 3D digital humans from monocular videos. Our method utilizes the efficiency of Gaussian splatting to model both 3D geometry and appearance. However, we observed that naiv