WebbOffice-Caltech10 : Office-Caltech10 contains ten object categories drawn from 4 image domains: Amazon (A), Webcam (W), DSLR (D), and Caltech256 (C). There are 8–151 samples per category per domain, and 2533 images in … WebbIn this paper, to address the first challenge, we propose a theoretical-guaranteed approach to combine domain experts locally trained on its own source domain to achieve a …

Office-Caltech-10 - V7 Open Datasets

Webbstate-of-the-art performance on the DomainNet and Office-Caltech10 datasets. The implementation code will be publicly available. 1 INTRODUCTION Deep Learning has drawn surging attention over the past decade. To solve the problem that deep models usually suffer from significant performance degradation when applied to an unseen target WebbWe make three major contributions towards addressing this problem. First, we propose a new deep learning approach, Moment Matching for Multi-Source Domain Adaptation (M3SDA), which aims to transfer knowledge learned from multiple labeled source domains to an unlabeled target domain by dynamically aligning moments of their feature … bishop stopford school kettering uk

Office-Caltech-10 Benchmark (Domain Adaptation) - Papers With …

http://ai.bu.edu/visda-2024/ Webb25 maj 2024 · Office-Caltech10 is a widely used real-world dataset for cross-domain object recognition . This dataset consists of object images taken from four domains: Amazon, DSLR, Webcam, and Caltech. Each domain has images represented by SURF features encoded with 800-bin bag-of-words histograms, of 10 object classes. WebbAlthough the proxy-A-distance with new representation decreases on Office-Caltech10 dataset, mSDA-AP achieves promising results on Office-Caltech10 dataset ... bishop stopford school twitter