4 accepted papers
Open-Vocabulary Temporal Action Detection (OV-TAD) aims to classify and localize action segments in untrimmed videos for unseen categories. Previous methods rely solely on global alignment between label-level semantics and visual features, which is insufficient to transfer temporal consistent visual
federated learning has been introduced into person re-identification (Re-ID) to avoid personal image leakage in traditional centralized training. To address the key issue of statistic heterogeneity in different clients, several optimization methods have been proposed to alleviate the bias of the loc…
Large-scale data from real-world usually follow a long-tailed distribution (i.e., a few majority classes occupy plentiful training data, while most minority classes have few samples), making the hyperplanes heavily skewed to the minority classes. Traditionally, reweighting is adopted to make the hyp…
Real-world data often follows a long-tailed distribution, which makes the performance of existing classification algorithms degrade heavily. A key issue is that the samples in tail categories fail to depict their intra-class diversity. Humans can imagine a sample in new poses, scenes and view angles…