6 papers
SC-Diff: Semantically Calibrated Diffusion for Visible-to-Infrared Image Translation
Junyin Zhang, Siyu Huang, Jianxiong Ye +4
Visible-to-infrared image translation provides a practical way to expand infrared training data using abundant visible images. Diffusion models are promising for this task because…
Registration-Grounded Spectral Fusion for Unregistered WLI/NBI Endoscopic Lesion Segmentation
Pengyu Jie, Wanquan Liu, Rui He +5
White-light imaging (WLI) and narrow-band imaging (NBI) provide complementary views of endoscopic lesions, but their paired observations are often spatially misaligned due to viewp…
Diffusion-Guided Mask-Consistent Paired Mixing for Endoscopic Image Segmentation
Pengyu Jie, Wanquan Liu, Rui He +3
Augmentation for dense prediction typically relies on either sample mixing or generative synthesis. Mixing improves robustness but misaligned masks yield soft label ambiguity. Diff…
IV-tuning: Parameter-Efficient Transfer Learning for Infrared-Visible Tasks
Yaming Zhang, Chenqiang Gao, Fangcen Liu +4
Existing infrared and visible (IR-VIS) methods inherit the general representations of Pre-trained Visual Models (PVMs) to facilitate complementary learning. However, our analysis i…
IVGF: The Fusion-Guided Infrared and Visible General Framework
Fangcen Liu, Chenqiang Gao, Fang Chen +3
Infrared and visible dual-modality tasks such as semantic segmentation and object detection can achieve robust performance even in extreme scenes by fusing complementary informatio…
Towards Student Actions in Classroom Scenes: New Dataset and Baseline
Zhuolin Tan, Chenqiang Gao, Anyong Qin +4
Analyzing student actions is an important and challenging task in educational research. Existing efforts have been hampered by the lack of accessible datasets to capture the nuance…