output
20172023
most citedReceptive Multi-granularity Representation for Person Re-Identification

30 citations

16 papers

cs.CV202329 cited

Boundary-aware Supervoxel-level Iteratively Refined Interactive 3D Image Segmentation with Multi-agent Reinforcement Learning

Chaofan Ma, Qisen Xu, Xiangfeng Wang +4

Interactive segmentation has recently been explored to effectively and efficiently harvest high-quality segmentation masks by iteratively incorporating user hints. While iterative…

cs.LG202326 cited

Discriminative Radial Domain Adaptation

Zenan Huang, Jun Wen, Siheng Chen +2

Domain adaptation methods reduce domain shift typically by learning domain-invariant features. Most existing methods are built on distribution matching, e.g., adversarial domain ad…

eess.IV20234 cited

Integrating features from lymph node stations for metastatic lymph node detection

Chaoyi Wu, Feng Chang, Xiao Su +4

Metastasis on lymph nodes (LNs), the most common way of spread for primary tumor cells, is a sign of increased mortality. However, metastatic LNs are time-consuming and challenging…

astro-ph.SR202223 cited

Eruptions from coronal bright points: A spectroscopic view by IRIS of a mini-filament eruption, QSL reconnection, and reconnection-driven outflows

Maria S. Madjarska, Duncan H. Mackay, Klaus Galsgaard +2

The present study investigates a mini-filament eruption associated with cancelling magnetic fluxes. The eruption originates from a small-scale loop complex commonly known as a Coro…

cs.LG20213 cited

Cooperative Learning for Noisy Supervision

Hao Wu, Jiangchao Yao, Ya Zhang +1

Learning with noisy labels has gained the enormous interest in the robust deep learning area. Recent studies have empirically disclosed that utilizing dual networks can enhance the…

cs.CV202111 cited

A Fourier-based Framework for Domain Generalization

Qinwei Xu, Ruipeng Zhang, Ya Zhang +2

Modern deep neural networks suffer from performance degradation when evaluated on testing data under different distributions from training data. Domain generalization aims at tackl…