1 citations · 1 across the 10 of their papers we have counts for
10 papers
Warp-free Cross-view Geo-localization via Feature-space Consensus Mining
Zhuo Song, Lian Xu, Runqing Jiang +4
Cross-view geo-localization is challenging due to drastic viewpoint changes and large appearance discrepancies between street-level and satellite imagery. Although existing methods…
ScalePredictor: Instance-aware Scale Learning for Accurate Quantization of Vision Transformers
Changjun Li, Runqing Jiang, Lian Xu +3
Vision Transformers have achieved remarkable success in many fields, yet their deployment on edge devices remains challenging due to their substantial computational demands. Post-T…
Triple Spectral Fusion for Sensor-based Human Activity Recognition
Ye Zhang, Longguang Wang, Qing Gao +3
The field of sensor-based human activity recognition (HAR) mainly uses posture, motion and context data of Inertial Measurement Units (IMUs) to identify daily activities. Despite t…
A Unified Hierarchical Framework for Fine-grained Cross-view Geo-localization over Large-scale Scenarios
Zhuo Song, Ye Zhang, Kunhong Li +2
Cross-view geo-localization is a promising solution for large-scale localization problems, requiring the sequential execution of retrieval and metric localization tasks to achieve…
Pack-PTQ: Advancing Post-training Quantization of Neural Networks by Pack-wise Reconstruction
Changjun Li, Runqing Jiang, Zhuo Song +3
Post-training quantization (PTQ) has evolved as a prominent solution for compressing complex models, which advocates a small calibration dataset and avoids end-to-end retraining. H…
Pluggable Style Representation Learning for Multi-Style Transfer
Hongda Liu, Longguang Wang, Weijun Guan +2
Due to the high diversity of image styles, the scalability to various styles plays a critical role in real-world applications. To accommodate a large amount of styles, previous mul…
SaMam: Style-aware State Space Model for Arbitrary Image Style Transfer
Hongda Liu, Longguang Wang, Ye Zhang +2
Global effective receptive field plays a crucial role for image style transfer (ST) to obtain high-quality stylized results. However, existing ST backbones (e.g., CNNs and Transfor…
Progressive Correspondence Regenerator for Robust 3D Registration
Guiyu Zhao, Sheng Ao, Ye Zhang +2
Obtaining enough high-quality correspondences is crucial for robust registration. Existing correspondence refinement methods mostly follow the paradigm of outlier removal, which ei…
AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers
Runqing Jiang, Ye Zhang, Longguang Wang +2
Post-training quantization (PTQ) has emerged as a promising solution for reducing the storage and computational cost of vision transformers (ViTs). Recent advances primarily target…
Preserving Full Degradation Details for Blind Image Super-Resolution
Hongda Liu, Longguang Wang, Ye Zhang +3
The performance of image super-resolution relies heavily on the accuracy of degradation information, especially under blind settings. Due to the absence of true degradation models…