2 citations · 3 across the 17 of their papers we have counts for
18 papers
MMUSV-Sim: A Perception-Oriented Simulation and Data-Generation Platform for Multi-USV Cooperative Perception
Ziao Li, Jianxiong Ye, Biao Tang +4
Cooperative perception among multiple unmanned surface vehicles (USVs) combines complementary observations to extend maritime target sensing beyond the view range and field of a si…
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…
ReUnit: Multi-Granularity Visual Unitization for Long Video Understanding
Biao Tang, Xu Chen, Shuxiang Gou +4
Long-video understanding is constrained by the limited visual input capacity of video multimodal large language models (Video-MLLMs). Existing methods mainly optimize which content…
WildGHand: Learning Anti-Perturbation Gaussian Hand Avatars from Monocular In-the-Wild Videos
Hanhui Li, Xuan Huang, Wanquan Liu +5
Despite recent progress in 3D hand reconstruction from monocular videos, most existing methods rely on data captured in well-controlled environments and therefore degrade in real-w…
SOFTooth: Semantics-Enhanced Order-Aware Fusion for Tooth Instance Segmentation
Xiaolan Li, Wanquan Liu, Pengcheng Li +2
Three-dimensional (3D) tooth instance segmentation remains challenging due to crowded arches, ambiguous tooth-gingiva boundaries, missing teeth, and rare yet clinically important t…
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…
AD-DINOv3: Enhancing DINOv3 for Zero-Shot Anomaly Detection with Anomaly-Aware Calibration
Jingyi Yuan, Jianxiong Ye, Wenkang Chen +1
Zero-Shot Anomaly Detection (ZSAD) seeks to identify anomalies from arbitrary novel categories, offering a scalable and annotation-efficient solution. Traditionally, most ZSAD work…
Dual-Branch Residual Network for Cross-Domain Few-Shot Hyperspectral Image Classification with Refined Prototype
Anyong Qin, Chaoqi Yuan, Qiang Li +3
Convolutional neural networks (CNNs) are effective for hyperspectral image (HSI) classification, but their 3D convolutional structures introduce high computational costs and limite…
AFR-CLIP: Enhancing Zero-Shot Industrial Anomaly Detection with Stateless-to-Stateful Anomaly Feature Rectification
Jingyi Yuan, Chenqiang Gao, Pengyu Jie +3
Recently, zero-shot anomaly detection (ZSAD) has emerged as a pivotal paradigm for industrial inspection and medical diagnostics, detecting defects in novel objects without requiri…
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…