2 citations · 3 across the 11 of their papers we have counts for
11 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 cues for endoscopic lesion segmentation, yet their sequential acquisition often results in spatially i…
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…
DPDETR: Decoupled Position Detection Transformer for Infrared-Visible Object Detection
Junjie Guo, Chenqiang Gao, Fangcen Liu +1
Infrared-visible object detection aims to achieve robust object detection by leveraging the complementary information of infrared and visible image pairs. However, the commonly exi…
A Point-Neighborhood Learning Framework for Nasal Endoscope Image Segmentation
Pengyu Jie, Wanquan Liu, Chenqiang Gao +6
Lesion segmentation on nasal endoscopic images is challenging due to its complex lesion features. Fully-supervised deep learning methods achieve promising performance with pixel-le…
DAMSDet: Dynamic Adaptive Multispectral Detection Transformer with Competitive Query Selection and Adaptive Feature Fusion
Junjie Guo, Chenqiang Gao, Fangcen Liu +2
Infrared-visible object detection aims to achieve robust even full-day object detection by fusing the complementary information of infrared and visible images. However, highly dyna…
Are Dense Labels Always Necessary for 3D Object Detection from Point Cloud?
Chenqiang Gao, Chuandong Liu, Jun Shu +5
Current state-of-the-art (SOTA) 3D object detection methods often require a large amount of 3D bounding box annotations for training. However, collecting such large-scale densely-s…
InfMAE: A Foundation Model in the Infrared Modality
Fangcen Liu, Chenqiang Gao, Yaming Zhang +3
In recent years, the foundation models have swept the computer vision field and facilitated the development of various tasks within different modalities. However, it remains an ope…