most citedMobileMamba: Lightweight Multi-Receptive Visual Mamba Network

6 citations · 7 across the 4 of their papers we have counts for

collaborators

7 papers

astro-ph.HE2025

The magnetar model's energy crisis for a prolific repeating fast radio burst source

Jun-Shuo Zhang, Tian-Cong Wang, Pei Wang +61

Fast radio bursts (FRBs) are widely considered to originate from magnetars that power the explosion through releasing magnetic energy. Active repeating FRBs have been seen to produ…

astro-ph.HE2025

Investigating FRB 20240114A with FAST: Morphological Classification and Drifting Rate Measurements in a Burst-Cluster Framework

Long-Xuan Zhang, Shiyan Tian, Junyi Shen +59

This study investigates the morphological classification and drifting rate measurement of the repeating fast radio burst (FRB) source FRB 20240114A using the Five-hundred-meter Ape…

cs.CV2025

OracleFusion: Assisting the Decipherment of Oracle Bone Script with Structurally Constrained Semantic Typography

Caoshuo Li, Zengmao Ding, Xiaobin Hu +10

As one of the earliest ancient languages, Oracle Bone Script (OBS) encapsulates the cultural records and intellectual expressions of ancient civilizations. Despite the discovery of…

cs.CV2025

Few-Shot Anomaly-Driven Generation for Anomaly Classification and Segmentation

Guan Gui, Bin-Bin Gao, Jun Liu +2

Anomaly detection is a practical and challenging task due to the scarcity of anomaly samples in industrial inspection. Some existing anomaly detection methods address this issue by…

cs.CV20246 cited

MobileMamba: Lightweight Multi-Receptive Visual Mamba Network

Haoyang He, Jiangning Zhang, Yuxuan Cai +7

Previous research on lightweight models has primarily focused on CNNs and Transformer-based designs. CNNs, with their local receptive fields, struggle to capture long-range depende…

cs.CV20241 cited

FitDiT: Advancing the Authentic Garment Details for High-fidelity Virtual Try-on

Boyuan Jiang, Xiaobin Hu, Donghao Luo +7

Although image-based virtual try-on has made considerable progress, emerging approaches still encounter challenges in producing high-fidelity and robust fitting images across diver…