381 citations · 526 across the 2 of their papers we have counts for
2 papers
cs.CV2023★ 145 cited
HRTransNet: HRFormer-Driven Two-Modality Salient Object Detection
Bin Tang, Zhengyi Liu, Yacheng Tan +1
The High-Resolution Transformer (HRFormer) can maintain high-resolution representation and share global receptive fields. It is friendly towards salient object detection (SOD) in w…
cs.CV2022★ 381 cited
SwinNet: Swin Transformer drives edge-aware RGB-D and RGB-T salient object detection
Zhengyi Liu, Yacheng Tan, Qian He +1
Convolutional neural networks (CNNs) are good at extracting contexture features within certain receptive fields, while transformers can model the global long-range dependency featu…